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Tesi sul tema "Receiver Operating Characteristic (ROC) Curve"
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1
Caswell, Benjamin C. "Receiver Operating Characteristic (ROC) Curve Analysis of Affinity Profiles". Diss., CLICK HERE for online access, 2009. http://contentdm.lib.byu.edu/ETD/image/etd3012.pdf.
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Zhang, Zheng. "Semiparametric least squares analysis of the receiver operating characteristic curve /". Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/9578.
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Dodd, Lori Elizabeth. "Regression methods for areas and partial areas under the receiver-operating characteristic curve /". Thesis, Connect to this title online; UW restricted, 2001. http://hdl.handle.net/1773/9567.
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4
BORGSTROM, MARK CRAIG. "ESTIMATION OF RECEIVER OPERATING CHARACTERISTIC (ROC) CURVE PARAMETERS: SMALL SAMPLE PROPERTIES OF ESTIMATORS". Diss., The University of Arizona, 1987. http://hdl.handle.net/10150/184127.
Testo completoAbstract (sommario):
When studying detection systems, parameters associated with the Receiver Operating Characteristic (ROC) curve are often estimated to assess system performance. In some applied settings it is often not possible to test the detection system with large numbers of stimuli. The resulting small sample statistics many have undesirable properties. The characteristics of these small sample ROC estimators were examined in a Monte Carlo simulation. Three popular ROC parameters were chosen for study. One of the parameters was a single parameter index of system performance, Area under the ROC curve. The other parameters, ROC intercept and slope, were considered as a pair. ROC intercept and slope were varied along with sample size and points on the certainty rating scale to form a four way factorial design. Several types of estimators were examined. For the parameter, Area under the curve, Maximum Likelihood (ML), three types of Least Squares (LS), and Distribution Free (DF) estimators were considered. Except for the DF estimator, the same estimators were considered for the parameters, intercept and slope. These estimators were compared with respect to three characteristics: bias, efficiency, and consistency. For Area under the curve, the ML estimator was the least biased. The DF estimator was the most efficient, and all the estimators except the DF estimator appeared to be consistent. For intercept and slope the LS estimator that minimized vertical error of the points from the ROC curve (line) was the least biased for both estimators. This LS estimator was also the most efficient. This estimator along with the ML estimator also appeared to be the most consistent. The other two estimators had no significant trend toward consistency. These results along with other findings, illustrate that different estimators may be "best" for different sample sizes and for different parameters. Therefore, researchers should carefully consider the characteristics of ROC estimators before using them as indices of system performance.
5
Peng, Hongying. "ROC Curves for Ordinal Biomarkers". University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1543582492604243.
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6
池田, 充., Takeo Ishigaki, Mitsuru Ikeda, 一信 山内 e Kazunobu Yamauchi. "Relationship between Brier score and area under the binormal ROC curve". Elsevier, 2002. http://hdl.handle.net/2237/5310.
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Liu, Hua. "ASYMPTOTIC PROPERTIES OF PARTIAL AREAS UNDER THE RECEIVER OPERATING CHARACTERISTIC CURVE WITH APPLICATIONS IN MICROARRAY EXPERIMENTS". UKnowledge, 2006. http://uknowledge.uky.edu/gradschool_diss/463.
Testo completoAbstract (sommario):
Receiver operating characteristic (ROC) curves are widely used in medical decision making. It was recognized in the last decade that only a specific region of the ROC curve is of clinical interest, which can be summarized by the partial area under the ROC curve (partial AUC). Early statistical methods for evaluating partial AUC assume that the data are from a specified underlying distribution. Nonparametric estimators of the partial AUC emerged recently, but there are theoretical issues to be addressed. In this dissertation, we propose two new nonparametric statistics, partially integrated ROC and partially integrated weighted ROC, for estimating partial AUC. We show that our partially integrated ROC statistic is a consistent estimator of the partial AUC, and derive its asymptotic distribution which is distribution free under the null hypothesis. In the partially integrated ROC statistic, when the ROC curve crosses the Uniform distribution function (CDF) and if the partial area evaluated contains the crossing point, or when there are multiple crossing, the partially integrated ROC statistic might not perform well. To address this issue, we propose the partially integrated weighted ROC statistic. This statistic evaluates the partially weighted AUC, where larger weight is given when the ROC curve is above the Uniform CDF and smaller weight is given when the ROC curve is below the Uniform CDF. We show that our partially integrated weighted ROC statistic is a consistent estimator of the partially weighted AUC. We derive its asymptotic distribution which is distribution free under the null hypothesis. We propose to apply our two nonparametric statistics to functional category analysis in microarray experiments. We define the functional category analysis to be the statistical identification of over-represented functional gene categories in a microarray experiment based on differential gene expression. We compare our statistics with existing methods for the functional category analysis both via simulation study and application to a real microarray data, and demonstrate that our two statistics are effective for identifying over-represented functional gene categories. We also emphasize the essential role of the empirical distribution function plots and the ROC curves in the functional category analysis.
8
Stacy, Catherine Ann. "Applying mixed-effects receiver operating characteristic (ROC) curve analysis to diagnostic evaluations of human learning". Access restricted to users with UT Austin EID Full text (PDF) from UMI/Dissertation Abstracts International, 2001. http://wwwlib.umi.com/cr/utexas/fullcit?p3035981.
Testo completo
9
Contini, Letizia. "Identificazione del danno in strutture reticolari via frequenze di vibrare e Receiver Operating Characteristic (ROC) curve". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.
Cerca il testo completoAbstract (sommario):
Il seguente elaborato affronta, nella sua prima parte, gli effetti che vari disturbi esterni ed incontrollabili, possono provocare sui parametri modali della struttura durante il monitoraggio dinamico, portando ad un'errata valutazione della salute di salute dell'opera.
Allo scopo di ridurre questo problema, nella seconda parte della tesi, viene analizzata una struttura reticolare in acciaio sottoposta a indice di danno, temperatura e livello di rumore variabile.
Tale modello è stato utilizzato per la ricerca di una metrica robusta che, indipendentemente dai disturbi esterni applicati, riesca a fornire una precisa ed esatta identificazione del danno strutturale, e quindi, conseguentemente, una valida valutazione dello stato di conservazione dell'opera.
Una volta eseguite tutte le analisi e valutazioni del caso, la relazione determinata è stata applicata a diverse tipologie di strutture, al fine di verificarne la sua validità.
Nell'ultima parte dell'elaborato sono state riportate le conclusioni, in cui si è validata l'analisi eseguita e i suoi conseguenti risultati.
10
Sun, Fangfang. "Semi-parametric inference for the partial area under the ROC curve". unrestricted, 2008. http://etd.gsu.edu/theses/available/etd-11192008-113213/.
Testo completoAbstract (sommario):
Thesis (M.S.)--Georgia State University, 2008.Title from file title page. Gengsheng Qin, committee chair; Yu-Sheng Hsu, Yixin Fang, Yuanhui Xiao, committee members. Description based on contents viewed July 22, 2009. Includes bibliographical references (p. 29-30).
11
Zhao, Hui. "Discrimination of High Risk and Low Risk Populations for the Treatment of STDs". Digital Archive @ GSU, 2011. http://digitalarchive.gsu.edu/math_theses/104.
Testo completoAbstract (sommario):
It is an important step in clinical practice to discriminate real diseased patients from healthy persons. It would be great to get such discrimination from some common information like personal information, life style, and the contact with diseased patient. In this study, a score is calculated for each patient based on a survey through generalized linear model, and then the diseased status is decided according to previous sexually transmitted diseases (STDs) records. This study will facilitate clinics in grouping patients into real diseased or healthy, which in turn will affect the method clinics take to screen patients: complete screening for possible diseased patient and some common screening for potentially healthy persons.
12
Young, Mimy. "Evaluation of Non-Contact Sampling and Detection of Explosives using Receiver Operating Characteristic Curves". FIU Digital Commons, 2013. http://digitalcommons.fiu.edu/etd/994.
Testo completoAbstract (sommario):
The growing need for fast sampling of explosives in high throughput areas has increased the demand for improved technology for the trace detection of illicit compounds. Detection of the volatiles associated with the presence of the illicit compounds offer a different approach for sensitive trace detection of these compounds without increasing the false positive alarm rate. This study evaluated the performance of non-contact sampling and detection systems using statistical analysis through the construction of Receiver Operating Characteristic (ROC) curves in real-world scenarios for the detection of volatiles in the headspace of smokeless powder, used as the model system for generalizing explosives detection. A novel sorbent coated disk coined planar solid phase microextraction (PSPME) was previously used for rapid, non-contact sampling of the headspace containers. The limits of detection for the PSPME coupled to IMS detection was determined to be 0.5-24 ng for vapor sampling of volatile chemical compounds associated with illicit compounds and demonstrated an extraction efficiency of three times greater than other commercially available substrates, retaining >50% of the analyte after 30 minutes sampling of an analyte spike in comparison to a non-detect for the unmodified filters. Both static and dynamic PSPME sampling was used coupled with two ion mobility spectrometer (IMS) detection systems in which 10-500 mg quantities of smokeless powders were detected within 5-10 minutes of static sampling and 1 minute of dynamic sampling time in 1-45 L closed systems, resulting in faster sampling and analysis times in comparison to conventional solid phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS) analysis. Similar real-world scenarios were sampled in low and high clutter environments with zero false positive rates. Excellent PSPME-IMS detection of the volatile analytes were visualized from the ROC curves, resulting with areas under the curves (AUC) of 0.85-1.0 and 0.81-1.0 for portable and bench-top IMS systems, respectively. Construction of ROC curves were also developed for SPME-GC-MS resulting with AUC of 0.95-1.0, comparable with PSPME-IMS detection. The PSPME-IMS technique provides less false positive results for non-contact vapor sampling, cutting the cost and providing an effective sampling and detection needed in high-throughput scenarios, resulting in similar performance in comparison to well-established techniques with the added advantage of fast detection in the field.
13
池田, 充., Mitsuru Ikeda, 茂樹 伊藤, Shigeki Ito, 武男 石垣, Takeo Ishigaki, Kazunobu Yamauchi e 一信 山内. "Evaluation of a neural network classifier for pancreatic masses based on CT findings". Elsevier, 1997. http://hdl.handle.net/2237/5311.
Testo completo
14
Khamesipour, Alireza. "IMPROVED GENE PAIR BIOMARKERS FOR MICROARRAY DATA CLASSIFICATION". OpenSIUC, 2018. https://opensiuc.lib.siu.edu/dissertations/1573.
Testo completoAbstract (sommario):
The Top Scoring Pair (TSP) classifier, based on the notion of relative ranking reversals in the expressions of two marker genes, has been proposed as a simple, accurate, and easily interpretable decision rule for classification and class prediction of gene expression profiles. We introduce the AUC-based TSP classifier, which is based on the Area Under the ROC (Receiver Operating Characteristic) Curve. The AUCTSP classifier works according to the same principle as TSP but differs from the latter in that the probabilities that determine the top scoring pair are computed based on the relative rankings of the two marker genes across all subjects as opposed to for each individual subject. Although the classification is still done on an individual subject basis, the generalization that the AUC-based probabilities provide during training yield an overall better and more stable classifier. Through extensive simulation results and case studies involving classification in ovarian, leukemia, colon, and breast and prostate cancers and diffuse large b-cell lymphoma, we show the superiority of the proposed approach in terms of improving classification accuracy, avoiding overfitting and being less prone to selecting non-informative pivot genes. The proposed AUCTSP is a simple yet reliable and robust rank-based classifier for gene expression classification. While the AUCTSP works by the same principle as TSP, its ability to determine the top scoring gene pair based on the relative rankings of two marker genes across {\em all} subjects as opposed to each individual subject results in significant performance gains in classification accuracy. In addition, the proposed method tends to avoid selection of non-informative (pivot) genes as members of the top-scoring pair.\\ We have also proposed the use of the AUC test statistic in order to reduce the computational cost of the TSP in selecting the most informative pair of genes for diagnosing a specific disease. We have proven the efficacy of our proposed method through case studies in ovarian, colon, leukemia, breast and prostate cancers and diffuse large b-cell lymphoma in selecting informative genes. We have compared the selected pairs, computational cost and running time and classification performance of a subset of differentially expressed genes selected based on the AUC probability with the original TSP in the aforementioned datasets. The reduce sized TSP has proven to dramatically reduce the computational cost and time complexity of selecting the top scoring pair of genes in comparison to the original TSP in all of the case studies without degrading the performance of the classifier. Using the AUC probability, we were able to reduce the computational cost and CPU running time of the TSP by 79\% and 84\% respectively on average in the tested case studies. In addition, the use of the AUC probability prior to applying the TSP tends to avoid the selection of genes that are not expressed (``pivot'' genes) due to the imposed condition. We have demonstrated through LOOCV and 5-fold cross validation that the reduce sized TSP and TSP have shown to perform approximately the same in terms of classification accuracy for smaller threshold values. In conclusion, we suggest the use of the AUC test statistic in reducing the size of the dataset for the extensions of the TSP method, e.g. the k-TSP and TST, in order to make these methods feasible and cost effective.
15
Celidoni, Martina. "Essays on vulnerability to poverty and inequality". Doctoral thesis, Università degli studi di Padova, 2012. http://hdl.handle.net/11577/3422143.
Testo completoAbstract (sommario):
According to the recent report of The Commission on the Measurement of Economic Performance and Social Progress (CMEPSP), whose members are also Joseph Stiglitz, Amartya Sen and Jean Paul Fitoussi, statistical indicators are important for designing and assessing policies aiming at advancing the progress of society (Stiglitz, Sen, and Fitoussi, 2009).
The main objective of the present work is to shed light on some aspects concerning the information provided by vulnerability to poverty and inequality indexes.
The first chapter compares empirically the several measures of individual vulnerability to poverty proposed in the literature, in order to understand which is the best signal of poverty that can be used for policies purposes. To this aim the Receiver Operating Characteristic (ROC) curve, the Pearson and Spearman correlation coefficients are used as precision criteria. Using data from the British Household Panel Survey (BHPS), the German Socio-Economic Panel (SOEP) and the Survey on Household Income and Wealth (SHIW), the results show that two groups of indexes can be identified, high- and low-performers, and, among the former, that proposed by Dutta, Foster, and Mishra (2011) is the most precise.
The second chapter applies a non-parametric decomposition of the Foster-Greer-Thorbecke poverty index to the measurement of individual vulnerability to poverty. I highlight that poverty risk can be expressed as a function of three components expected incidence, expected intensity and expected downward variability. This decomposition is useful for risk management purposes since it describes the characteristics of the poverty risk faced by individuals. An empirical illustration is provided using the British Household Panel Survey and the Survey on Household Income and Wealth.
The third chapter focuses on inequality. According to Atkinson (1971), inequality attributable to age should be of little concern for policymakers because it is irrelevant for the distribution of lifetime income or wealth. Concerning that I provide age-adjusted measures of wealth inequality to understand the role of demographic changes in Italy in determining the trends in disparities. Using the Survey on Household Income and Wealth from 1991 to 2008, the results confirm previous findings: age-adjustments are not very important in terms of dynamics.Alla luce del recente rapporto della Commissione sulla Misura della Performance Economica e del progresso Sociale (CMEPSP), composta anche da Joseph Stiglitz, Amartya Sen e Jean Paul Fitoussi, gli indicatori statistici sono importanti per il design e la valutazione delle politiche pubbliche in termini di progresso sociale (Stiglitz, Sen, and Fitoussi, 2009). L'obiettivo principale della tesi in oggetto è l'analisi dell'informazione fornita dagli indici di vulnerabilità alla povertà e disuguaglianza. Il primo capitolo confronta in termini empirici le misure individuali di vulnerabilità alla povertà proposte in letteratura. Lo scopo è capire quale sia l'indice più preciso nel predire la povertà, affinchè questo possa essere utilizzato come fonte di informazione per le politiche pubbliche. La Receiver Operating Characteristic (ROC) curve, i coefficenti di correlazione di Pearson e Spearman sono utilizzati come criteri per la valutazione della precisione. Usando dati del British Household Panel Survey (BHPS), del German Socio-Economic Panel (SOEP) e della Survey on Household Income and Wealth (SHIW), i risultati mostrano che possono essere identificate due categorie di indici, high- e low-performers; fra i primi, l'indice proposto da Dutta, Foster, and Mishra (2011) è il più preciso nell'identificare i futuri poveri. Il secondo capitolo applica una scomposizione non parametrica dell'indice di povertà Foster-Greer-Thorbecke alla vulnerabilità alla povertà individuale. Questo approccio mostra come il rischio di povertà può essere espresso come funzione di incidenza attesa, intensità attesa e variabilità negativa attesa. La scomposizione proposta è utile in termini di politiche di risk management per le informazioni circa le caratteristiche del rischio di povertà. Il capitolo prevede due illustrazioni empiriche con dati del British Household Panel Survey e della Survey on Household Income and Wealth. Il terzo capitolo di focalizza sugli indici di disuguaglianza. Secondo Atkinson (1971), la disuguaglianza attribuibile all'età è irrilevante se l'interesse è concentrato nella distribuzione di reddito e ricchezza di lungo periodo (lifetime perspective). Riguardo ciò, il terzo capitolo propone delle misure di disuguaglianza basate sulla ricchezza netta e corrette per l'effetto dei cambiamenti demografici nella popolazione italiana fra il 1991 ed il 2008. Utilizzando i dati della Survey on Household Income and Wealth della Banca d'Italia, i risultati confermano quanto già osservato in letteratura: gli aggiustamenti demografici non risultano determinanti nella dinamica della disuguaglianza in termini di ricchezza netta.
16
Herath, Dushanthi N. "Nonparametric Estimation of Receiver Operating Characteristic Surfaces Via Bernstein Polynomials". Thesis, University of North Texas, 2012. https://digital.library.unt.edu/ark:/67531/metadc177212/.
Testo completoAbstract (sommario):
Receiver operating characteristic (ROC) analysis is one of the most widely used methods in evaluating the accuracy of a classification method. It is used in many areas of decision making such as radiology, cardiology, machine learning as well as many other areas of medical sciences. The dissertation proposes a novel nonparametric estimation method of the ROC surface for the three-class classification problem via Bernstein polynomials. The proposed ROC surface estimator is shown to be uniformly consistent for estimating the true ROC surface. In addition, it is shown that the map from which the proposed estimator is constructed is Hadamard differentiable. The proposed ROC surface estimator is also demonstrated to lead to the explicit expression for the estimated volume under the ROC surface . Moreover, the exact mean squared error of the volume estimator is derived and some related results for the mean integrated squared error are also obtained. To assess the performance and accuracy of the proposed ROC and volume estimators, Monte-Carlo simulations are conducted. Finally, the method is applied to the analysis of two real data sets.
17
Ren, Peng. "Off-line and On-line Affective Recognition of a Computer User through A Biosignal Processing Approach". FIU Digital Commons, 2013. http://digitalcommons.fiu.edu/etd/838.
Testo completoAbstract (sommario):
Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet.
In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment (“relaxation” vs. “stress”) are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90.
For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation).
In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the “relaxation” vs. “stress” states.
18
Blangero, Yoann. "Méthodologie de l’évaluation des biomarqueurs prédictifs quantitatifs et de la détermination d’un seuil pour leur utilisation en médecine personnalisée". Thesis, Lyon, 2019. http://www.theses.fr/2019LYSE1125/document.
Testo completoAbstract (sommario):
En France, la recherche contre le cancer est un enjeu majeur de santé publique. On estime notamment que le nombre de nouveaux cas de cancer a plus que doublé entre 1980 et 2012. L’hétérogénéité des caractéristiques tumorales, pour un même cancer, impose des défis complexes dans la recherche de traitements efficaces. Dans ce contexte, des espoirs importants sont placés dans la recherche de biomarqueurs prédictifs reflétant les caractéristiques des patients ainsi que de leur tumeur afin d’orienter le choix de la stratégie thérapeutique. Par exemple, pour les cancers colorectaux métastatiques, il est maintenant reconnu que l’ajout de cetuximab (un anti-EGFR) à la chimiothérapie classique (ici le FOLFOX4), n’apporte un bénéfice qu’aux patients dont le gène KRAS est non muté. Le gène KRAS est ici un biomarqueur prédictif binaire, mais de nombreux biomarqueurs sont le résultat d’une quantification ou d’un dosage. L’objectif de cette thèse est dans un premier temps, de quantifier la capacité globale d’un biomarqueur quantitatif à guider le choix du traitement. Après une revue de la littérature, une nouvelle méthode basée sur une extension des courbes ROC est proposée, et comparée aux méthodes existantes. Son principal avantage est d’être non paramétrique, et d’être indépendante de l’efficacité moyenne des traitements. Dans un second temps, lorsqu’un biomarqueur prédictif quantitatif est étudié, la définition d’un seuil de marqueur au-delà duquel la première option de traitement sera préférée, et en-deçà duquel la deuxième option de traitement sera préférée se pose. Une approche reposant sur la définition d’une fonction d’utilité est proposée permettant alors de tenir compte de l’efficacité des traitements ainsi que de leur impact sur la qualité de vie des patients. Une méthode Bayésienne d’estimation de ce seuil optimal est proposéeIn France, the cancer research is a major public health issue. The number of new cancer cases nearly doubled between 1980 and 2012. The heterogeneity of the tumor characteristics, for a given cancer, presents a great challenge in the research of new effective treatments. In this context, much hope is placed in the research of predictive (or treatment selection) biomarkers that reflect the patients’ characteristics in order to guide treatment choice. For example, in the metastatic colorectal cancer setting, it is admitted that the addition of cetuximab (an anti-EGFR) to classical chemotherapy (the FOLFOX4), only improve the outcome of patients with KRAS wild-type tumors. In that context, the KRAS gene is a binary treatment selection marker, but plenty of biomarkers result from some quantifications or dosage measurements. The first aim of this thesis is to quantify the global treatment selection ability of a biomarker. After a review of the existing litterature, a method based on an extension of ROC curves is proposed and compared to existing methods. Its main advantage is that it is non-parametric, and that it does not depend on the mean risk of event in each treatment arm. In a second time, when a quantitative treatment selection biomarker is assessed, there is a need to estimate a marker thereshold value above which one treatment is preferred, and below which the other treatment is recommended. An approach that relies on the definition of a utility function is proposed in order to take into account both efficacy and toxicity of treatments when estimating the optimal threshold. A Bayesian method for the estimation of the optimal threshold is proposed
19
Murnane, Owen D., Faith W. Akin, S. D. Lynn e D. G. Cyr. "“Monothermal caloric screening test performance: A relative operating characteristic (ROC) curve analysis". Digital Commons @ East Tennessee State University, 2009. https://dc.etsu.edu/etsu-works/1893.
Testo completo
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Yu, Daoping. "Early Stopping of a Neural Network via the Receiver Operating Curve". Digital Commons @ East Tennessee State University, 2010. https://dc.etsu.edu/etd/1732.
Testo completoAbstract (sommario):
This thesis presents the area under the ROC (Receiver Operating Characteristics) curve, or abbreviated AUC, as an alternate measure for evaluating the predictive performance of ANNs (Artificial Neural Networks) classifiers. Conventionally, neural networks are trained to have total error converge to zero which may give rise to over-fitting problems. To ensure that they do not over fit the training data and then fail to generalize well in new data, it appears effective to stop training as early as possible once getting AUC sufficiently large via integrating ROC/AUC analysis into the training process. In order to reduce learning costs involving the imbalanced data set of the uneven class distribution, random sampling and k-means clustering are implemented to draw a smaller subset of representatives from the original training data set. Finally, the confidence interval for the AUC is estimated in a non-parametric approach.
21
Wang, Wen-Chyi. "Regularized variable selection in proportional hazards model using area under receiver operating characteristic curve criterion". College Park, Md.: University of Maryland, 2009. http://hdl.handle.net/1903/9972.
Testo completoAbstract (sommario):
Thesis (Ph. D.) -- University of Maryland, College Park, 2009.Thesis research directed by: Dept. of Mathematics. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
22
Murnane, Owen D., Faith W. Akin, Susan G. Lynn e David G. Cyr. "Monothermal Caloric Screening Test Performance: A Relative Operating Characteristic Curve Analysis". Digital Commons @ East Tennessee State University, 2009. https://dc.etsu.edu/etsu-works/1788.
Testo completoAbstract (sommario):
Objective: The objective of the present study was to evaluate the performance of the monothermal caloric screening test in a large sample of patients.
Design: A retrospective analysis of the medical records of 1002 consecutive patients who had undergone vestibular assessment at the Mayo Clinic during the years 1989 and 1990 was conducted. Patients with incomplete alternate binaural bithermal (ABB) caloric testing, congenital or periodic alternating nystagmus, or bilateral vestibular loss were excluded from the study. Clinical decision theory analyses (relative operating characteristic curves) were used to determine the accuracy with which the monothermal warm (MWST) and monothermal cool (MCST) caloric screening tests predicted the results of the ABB caloric test. Cumulative distributions were constructed as a function of the cutoff points for monothermal interear difference (IED) to select the cutoff point associated with any combination of true-positive and false-positive rates.
Results: Both MWST and MCST performed well above chance level. The test performance for the MWST was significantly better than that of the MCST for three of the four ABB gold standards. A 10% IED cutoff point for the MWST yielded a false-negative rate of either 1% (UW ≥25%) or 3% (UW ≥20%). The use of a 10% IED (UW ≥25%) for the MWST would have resulted in a 40% reduction (N = 294) in the number of ABB caloric tests performed on patients without a unilateral weakness.
Conclusions: The results of this study indicated that the MWST decreases test time without sacrificing the sensitivity of the ABB caloric test.
23
Erte, Idil. "Bivariate Random Effects And Hierarchical Meta-analysis Of Summary Receiver Operating Characteristic Curve On Fine Needle Aspiration Cytology". Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613619/index.pdf.
Testo completoAbstract (sommario):
In this study, meta-analysis of diagnostic tests, Summary Receiver Operating Characteristic (SROC) curve, bivariate random effects and Hierarchical Summary Receiver Operating Characteristic (HSROC) curve theories have been discussed and accuracy in literature of Fine Needle Aspiration (FNA) biopsy that is used in the diagnosis of masses in breast cancer (malignant or benign) has been analyzed. FNA Cytological (FNAC) examination in breast tumor is, easy, effective, effortless, and does not require special training for clinicians. Because of the uncertainty related to FNAC&lsquos accurate usage in publications, 25 FNAC studies have been gathered in the meta-analysis. In the plotting of the summary ROC curve, the logit difference and sums of the true positive rates and the false positive rates included in the meta-analysis&lsquo
s codes have been generated by SAS. The formula of the bivariate random effects model and hierarchical summary ROC curve is presented in context with the literature. Then bivariate random effects implementation with the new SAS PROC GLIMMIX is generated. Moreover, HSROC implementation is generated by SAS PROC HSROC NLMIXED. Curves are plotted with RevMan Version 5 (2008). It has been stated that the meta-analytic results of bivariate random effects are nearly identical to the results from the HSROC approach. The results achieved through both random effects meta-analytic methods prove that FNA Cytology is a diagnostic test with a high level of distinguish over breast tumor.
24
Brown, Connolly Nancy. "Application of receiver operating characteristic analysis to a remote monitoring model for chronic obstructive pulmonary disease to determine utility and predictive value". Thesis, Brunel University, 2013. http://bura.brunel.ac.uk/handle/2438/8057.
Testo completoAbstract (sommario):
This is a foundational study that applies Receiver Operating Characteristic (ROC) analysis to the evaluation of a chronic disease model that utilizes Remote Monitoring (RM) devices to identify clinical deterioration in a Chronic Obstructive Pulmonary Disease (COPD) population. Background: RM programmes in Disease Management (DM) are proliferating as one strategy to address management of chronic disease. The need to validate and quantify evidence-based value is acute. There is a need to apply new methods to better evaluate automated RM systems. ROC analysis is an engineering approach that has been widely applied to medical programmes but has not been applied to RM systems. Evaluation of classifiers, determination of thresholds and predictive accuracy for RM systems have not been evaluated using ROC analysis. Objectives: (1) apply ROC analysis to evaluation of a RM system; (2) analyse the performance of the model when applied to patient outcomes for a COPD population; (3) identify predictive classifier(s); (4) identify optimal threshold(s) and the predictive capacity of the classifiers. Methods: Parametric and non-parametric methods are utilized to determine accuracy, sensitivity, specificity and predictive capacity of classifiers Saturated Peripheral Oxygen (SpO2), Blood Pressure (BP), Pulse Rate (PR) based on event-based patient outcomes that include hospitalisation (IP), accident & emergency (A&E) and home visits (HH). Population: Patients identified with a primary diagnosis of COPD, monitored for a minimum of 183 days with at least one episode of in-patient (IP) hospitalisation for COPD in the 12 months preceding the monitoring period. Data Source: A subset of retrospective de-identified patient data from an NHS Direct evaluation of a COPD RM programme. Subsets utilized include classifiers, biometric readings, alerts generated by the system and resource utilisation. Contribution: Validates ROC methodology, identifies classifier performance and optimal threshold settings for the classifier, while making design recommendations and putting forth the next steps for research. The question answered by this research is that ROC analysis can provide additional information on the predictive capacity of RM systems. Justification of benefit: The results can be applied when evaluating health services and planning decisions on the costs and benefits. Methods can be applied to system design, protocol development, work flows and commissioning decisions based on value and benefit. Conclusion: Results validate the use of ROC analysis as a robust methodology for DM programmes that use RM devices to evaluate classifiers, thresholds and identification of the predictive capacity as well as identify areas where additional design may improve the predictive capacity of the model.
25
Xu, Ping. "Evaluation of Repeated Biomarkers: Non-parametric Comparison of Areas under the Receiver Operating Curve Between Correlated Groups Using an Optimal Weighting Scheme". Scholar Commons, 2012. http://scholarcommons.usf.edu/etd/4261.
Testo completoAbstract (sommario):
Receiver Operating Characteristic (ROC) curves are often used to evaluate the prognostic performance of a continuous biomarker. In a previous research, a non-parametric ROC approach was introduced to compare two biomarkers with repeated measurements. An asymptotically normal statistic, which contains the subject-specific weights, was developed to estimate the areas under the ROC curve of biomarkers. Although two weighting schemes were suggested to be optimal when the within subject correlation is 1 or 0 by the previous study, the universal optimal weight was not determined. We modify this asymptotical statistic to compare AUCs between two correlated groups and propose a solution to weight optimization in non-parametric AUCs comparison to improve the efficiency of the estimator. It is demonstrated how the Lagrange multiplier can be used as a strategy for finding the weights which minimize the variance function subject to constraints. We show substantial gains of efficiency by using the novel weighting scheme when the correlation within group is high, the correlation between groups is high, and/or the disease incidence is small, which is the case for many longitudinal matched case-control studies. An illustrative example is presented to apply the proposed methodology to a thyroid function dataset. Simulation results suggest that the optimal weight performs well with a sample size as small as 50 per group.
26
Eissa, Salah. "Condition monitoring of pharmaceutical powder compression during tabletting using acoustic emission". Thesis, Brunel University, 2003. http://bura.brunel.ac.uk/handle/2438/5244.
Testo completoAbstract (sommario):
This research project aimed to develop a condition monitoring system for the final production quality of pharmaceutical tablets and detection capping and lamination during powder compression process using the acoustic emission (AE) method. Pharmaceutical tablet manufacturers obliged by regulatory bodies to test the tablet's physical properties such as hardness, dissolution and disintegration before the tablets are released to the market. Most of the existing methods and techniques for testing and monitoring these tablet's properties are performed at the tablet post-compression stage. Furthermore, these tests are destructive in nature. Early experimental investigations revealed that the AE energy that is generated during powder compression is directly proportional to the peak force that is required to crush the tablet, i. e. crushing strength. Further laboratory and industrial experimental investigation have been conducted to study the relationship between the AE signals and the compression conditions. Traditional AE signal features such as energy, count, peak amplitude, average signal level, event duration and rise time were recorded. AE data analysis with the aid of advanced classification algorithm, fuzzy C-mean clustering showed that the AE energy is a very useful parameter in tablet condition monitoring. It was found that the AE energy that is generated during powder compression is sensitive to the process and is directly proportional to the compression speed, particle size, homogeneity of mixture and the amount of material present. Also this AE signal is dependent upon the type of material used as the tablet filler. Acoustic emission has been shown to be a useful technique for characterising some of the complex physical changes which occur during tabletting. Capping and lamination are serious problems that are encountered during tabletting. A capped or laminated tablet is one which no longer retains its mechanical integrity and exhibit low strength characteristics. Capping and lamination can be caused by a number of factors such as excessive pressure, insufficient binder in the granules and poor material flowabilities. However, capping and lamination can also occur randomly and they are also dependent upon the material used in tabletting. It was possible to identify a capped or laminated tablet by monitoring the AE energy level during continuous on-line monitoring of tabletting. Capped tablets indicated by low level of AE energy. The proposed condition monitoring system aimed to set the AE energy threshold that could discriminate between capped and non-capped tablets. This was based upon statistical distributions of the AE energy values for both the capped and non-capped tablets. The system aims to minimise the rate of false alarms (indication of capping when in reality capping has not occurred) and the rate of missed detection (an indication of non capping, when in reality capping has occurred). A novel approach that employs both the AE method and the receiver operating characteristic (ROC) curve was proposed for the on-line detection of capping and lamination during tabletting. The proposed system employs AE energy as the discriminating parameter to detect between capped and non-capped tablets. The ROC curve was constructed from the area under the two distributions of both capped and non-capped tablet. This curve shows a trade-off between the probabilities of true detection rate and false alarm rate for capped and non-capped tablet. A two-graph receiver operating characteristic (ROC) curve was presented as a modification of the original ROC curve to enable an operator to directly select the desired energy threshold for tablet monitoring. This plot shows the ROC co-ordinate as a function of the threshold value over the entire threshold (AE energy) range for all test outcomes. An alternative way of deciding a threshold based on the slope of the ROC curve was also developed. The slope of the ROC curve represents the optimal operating point on the curve. It depends upon the penalties cost of capping and the prevalence of capping. Sets of guidelines have been outlined for decision making i.e. threshold setting. These guidelines take into account both the prevalence of capping in manufacturing and the cost associated with various outcomes of tablet formation. The proposed condition monitoring system also relates AE monitoring to non-AE measurement as it enable an operator predicting tablet hardness and disintegration form the AE energy, a relationship which was established in this research.
27
Jirwe, Marcus. "Online Anomaly Detection on the Edge". Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299565.
Testo completoAbstract (sommario):
The society of today relies a lot on the industry and the automation of factory tasks is more prevalent than ever before. However, the machines taking on these tasks require maintenance to continue operating. This maintenance is typically given periodically and can be expensive while sometimes requiring expert knowledge. Thus it would be very beneficial if one could predict when a machine needs maintenance and only employ maintenance as necessary. One method to predict when maintenance is necessary is to collect sensor data from a machine and analyse it for anomalies. Anomalies are usually an indicator of unexpected behaviour and can therefore show when a machine needs maintenance. Due to concerns like privacy and security, it is often not allowed for the data to leave the local system. Hence it is necessary to perform this kind of anomaly detection in an online manner and in an edge environment. This environment imposes limitations on hardware and computational ability. In this thesis we consider four machine learning anomaly detection methods that can learn and detect anomalies in this kind of environment. These methods are LoOP, iForestASD, KitNet and xStream. We first evaluate the four anomaly detectors on the Skoltech Anomaly Benchmark using their suggested metrics as well as the Receiver Operating Characteristic curves. We also perform further evaluation on two data sets provided by the company Gebhardt. The experimental results are promising and indicate that the considered methods perform well at the task of anomaly detection. We finally propose some avenues for future work, such as implementing a dynamically changing anomaly threshold.Dagens samhälle är väldigt beroende av industrin och automatiseringen av fabriksuppgifter är mer förekommande än någonsin. Dock kräver maskinerna som tar sig an dessa uppgifter underhåll för att forsätta arbeta. Detta underhåll ges typiskt periodvis och kan vara dyrt och samtidigt kräva expertkunskap. Därför skulle det vara väldigt fördelaktigt om det kunde förutsägas när en maskin behövde underhåll och endast göra detta när det är nödvändigt. En metod för att förutse när underhåll krävs är att samla in sensordata från en maskin och analysera det för att hitta anomalier. Anomalier fungerar ofta som en indikator av oväntat beteende, och kan därför visa att en maskin behöver underhåll. På grund av frågor som integritet och säkerhet är det ofta inte tillåtet att datan lämnar det lokala systemet. Därför är det nödvändigt att denna typ av anomalidetektering genomförs sekventiellt allt eftersom datan samlas in, och att detta sker på nätverkskanten. Miljön som detta sker i påtvingar begränsningar på både hårdvara och beräkningsförmåga. I denna avhandling så överväger vi fyra anomalidetektorer som med användning av maskininlärning lär sig och upptäcker anomalier i denna sorts miljö. Dessa metoder är LoOP, iForestASD, KitNet och xStream. Vi analyserar först de fyra anomalidetektorerna genom Skoltech Anomaly Benchmark där vi använder deras föreslagna mått samt ”Receiver Operating Characteristic”-kurvor. Vi genomför även vidare analys på två dataset som vi har tillhandhållit av företaget Gebhardt. De experimentella resultaten är lovande och indikerar att de övervägda metoderna presterar väl när det kommer till detektering av anomalier. Slutligen föreslår vi några idéer som kan utforskas för framtida arbete, som att implementera en tröskel för anomalidetektering som anpassar sig dynamiskt.
28
Cusumano, Carl Joseph. "Assessment of Residual Nonuniformity on Hyperspectral Target Detection Performance". University of Dayton / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1565137429596905.
Testo completo
29
Mattout, Jérémie. "Approches statistiques multivariées pour la localisation de l'activation cérébrale en magnétoencéphalographie et en imagerie par résonance magnétique fonctionnelle : vers une fusion d'informations multimodales". Paris 6, 2002. http://www.theses.fr/2002PA066440.
Testo completo
30
Pospíšil, Lukáš. "Analýza ROC křivek zvukových signálů a jejich srovnání". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2017. http://www.nusl.cz/ntk/nusl-316445.
Testo completoAbstract (sommario):
This thesis deals with oportunity of ROC curve usage in the description of methods that work with sound signals. Specifically, it focuses on ways of detecting of stress in speech signals. The detection itselfs is done in a range of frequencies of the sound signal. There is also a classifier designed using ROC curves that decides whether the input signal is stressed or not. The output of this thesis are findings gathered from analyses and also some recommendation based on those analyses.
31
Verdi, Marcio. "Prediçao de distribuíção de espécies arbustivo-arbóreas no sul do Brasil". reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2013. http://hdl.handle.net/10183/115515.
Testo completoAbstract (sommario):
Em vista das mudanças ambientais em nível global, disponibilizar informações ecológicas e buscar uma melhor compreensão dos fatores e processos que moldam a distribuição de espécies, é uma iniciativa importante para o planejamento de ações de conservação. Neste contexto, a importância e carência de informações sobre a distribuição geográficas das espécies nos motivaram a predizer a distribuição potencial de arbustos e árvores das famílias Lauraceae e Myrtaceae na Floresta Atlântica, no sul do Brasil. Modelos lineares generalizados (GLM) foram usados para ajustar modelos preditivos com os registros de ocorrência de 88 espécies em função de variáveis ambientais. As variáveis preditoras foram selecionadas com base no menor critério de informação de Akaike corrigido. Nós avaliamos o desempenho dos modelos usando o método de validação cruzada (10-fold) para calcular a habilidade estatística verdadeira (TSS) e a área sob a curva característica do operador receptor (AUC). Nós usamos GLM para testar a influência da área de ocorrência estimada, do número de registros das espécies e da complexidade dos modelos sobre a TSS e a AUC. Nossos resultados mostraram que as variáveis climáticas governam amplamente a distribuição de espécies, mas as variáveis que captam as variações ambientais locais são relativamente importantes na área de estudo. A TSS foi significativamente influenciada pelo número de registros e complexidade dos modelos, enquanto a AUC sofreu com o efeito de todos os três fatores avaliados. A interação entre estes fatores é uma questão importante e a ser considerada em novas avaliações sobre ambas medidas e com diferentes técnicas de modelagem. Nossos resultados também mostraram que as distribuições de algumas espécies foram superestimadas e outras corresponderam bem com a ocorrência por nós conhecida. Efetivamente nossos resultados têm fundamentos para embasar novos levantamentos de campo, a avaliação de áreas prioritárias e planos de conservação, além de inferências dos efeitos de mudanças ambientais sobre as espécies da Mata Atlântica.In view of environmental change on a global level, providing ecological information and getting a better understanding of the factors and processes that shape species distribution is an important initiative for planning conservation actions. In this context, the importance and lack of information about the geographical distribution of species motivated us to predict the potential species distribution of shrubs and trees of the family Lauraceae and Myrtaceae, in the Atlantic Forest in southern Brazil. Generalized linear models (GLM) were used to fit predictive models with records of occurrence of 88 species according to environmental variables. Predictor variables were selected based on the lowest corrected Akaike information criterion. We evaluate the performance of the models using the method of cross-validation (10-fold) to calculate the true skill statistic (TSS) and area under the receiver operator characteristic curve (AUC). We used GLM to test the influence of the area of occurrence estimated, the number of records of the species and the complexity of the models on the TSS and AUC. Our results show that climatic variables largely govern the distribution of species, but the variables that capture the local environmental variations are relatively important in the study area. The TSS was significantly influenced by the number of records and complexity of models while the AUC suffered from the effect of all three evaluated factors. The interaction between these factors is an important issue and be considered for new reviews on both measures and with different modeling techniques. Our results also showed that the distributions of some species were overestimated and other corresponded well with the occurrence known to us. Indeed our results have foundations to support new field surveys, assessment of priority areas and conservation plans, and inferences of the effects of environmental change on species of the Atlantic Forest.
32
Nalavolu, Praveen Reddy. "PERFORMANCE ANALYSIS OF SRCP IMAGE BASED SOUND SOURCE DETECTION ALGORITHMS". UKnowledge, 2010. http://uknowledge.uky.edu/gradschool_theses/50.
Testo completoAbstract (sommario):
Steered Response Power based algorithms are widely used for finding sound source location using microphone array systems. SRCP-PHAT is one such algorithm that has a robust performance under noisy and reverberant conditions. The algorithm creates a likelihood function over the field of view. This thesis employs image processing methods on SRCP-PHAT images, to exploit the difference in power levels and pixel patterns to discriminate between sound source and background pixels. Hough Transform based ellipse detection is used to identify the sound source locations by finding the centers of elliptical edge pixel regions typical of source patterns. Monte Carlo simulations of an eight microphone perimeter array with single and multiple sound sources are used to simulate the test environment and area under receiver operating characteristic (ROCA) curve is used to analyze the algorithm performance. Performance was compared to a simpler algorithm involving Canny edge detection and image averaging and an algorithms based simply on the magnitude of local maxima in the SRCP image. Analysis shows that Canny edge detection based method performed better in the presence of coherent noise sources.
33
LETO, BARONE Maria Stefania. "Analysis of a database to predict the result of allergy testing in vivo in patients with chronic nasal symptoms and the development of the software ARSTAT". Doctoral thesis, Università degli Studi di Palermo, 2014. http://hdl.handle.net/10447/91193.
Testo completoAbstract (sommario):
Background. This thesis consist of parts(i)Introduction in wich we present the clinical problem of rhinitis;(ii)the methods to evaluate the diagnostic choises;(iii)the rational errors in Allergy,(iv)the experimental part of thesis with wich we developed the software ARTSTAT,wich is the application of the analysis reported.Objective: We studied the ability of the logistic regression model obtained by the evaluaqtion of a database, to detect patients with positive allergy skin prick test(SPT)and patients with negative SPT. The model developed was valitated using the data set obtained from another medical institution. Methods: The analysis was carried out using a database obtained from a questionnaire administered to the patients with nasal symptoms containing personal data, clinical data result of allergy testing (SPT). All variables found to be significantly different between patients with positive and negative SPT(P<0.05),were selected for the logistic regression models and were analyzed with bacward stepwise logistic regression. A second set of patients from another Institution was used to prove the model. Results: e accuracyof the model identifying, over the second set, both patients whose SPT will bepositive and negative was high. The model detect 96 percent of patients with nasal symptoms and positive SPT, and classified 94 percent of those with negative SPT. Conclusion:The data of the thesis have been preliminary to the creation of a softwarewich cuold help the primary care doctors in diagnostic decision making process ( need of allergy testing), in patients complaining of chronic nasal symptoms.
34
Holtmann, Martin, Andreas Becker, Tobias Banaschewski, Aribert Rothenberger e Veit Rößner. "Psychometric Validity of the Strengths and Difficulties Questionnaire-Dysregulation Profile". Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-134171.
Testo completoAbstract (sommario):
Background: In many severely mentally disordered children, the clinical presentation is complicated by comorbid affective and behavioral dysregulation. Recently, a highly heritable behavioral phenotype of simultaneous deviance on the anxious/depressed, attention problems, and aggressive behavior syndrome scales has been identified on the Child Behavior Checklist Dysregulation Profile (CBCL-DP). The aim of the present pilot study was to determine an equivalent to the CBCL-DP using the Strengths and Difficulties Questionnaire (SDQ). Sampling and Methods: We applied stepwise linear discriminant analyses and receiver operating characteristic (ROC) analysis to data from 543 consecutively referred children and adolescents, aged 5–17 years. The CBCL and the SDQ were completed by parents as part of the diagnostic routine. ICD-10 discharge diagnoses were established in consensus conferences. Results: A combination of five SDQ items (SDQ-Dysregulation Profile, SDQ-DP) yielded the best discrimination of children with and without CBCL-DP and classified 81.0% of the subjects correctly leading to an area under the curve of 0.93. The content of the five SDQ-DP items mirrors well the mixed behavioral phenotype of anxious-depressive, aggressive and attention problems captured by the CBCL-DP. SDQ-DP status was highly correlated with CBCL-DP status and was best defined by a SDQ-DP score ≧5. Conclusions: The psychometric properties of the SDQ-DP have been robustly tested and validated. Based on these results, clinicians may use the SDQ-DP as a useful and economical screening measure to improve the assessment, prevention, and treatment of severe dysregulation in childhood and adolescence. Future investigations should study the longitudinal stability, heritability, and genetic associations of this behavioral phenotypeDieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich
35
Holtmann, Martin, Andreas Becker, Tobias Banaschewski, Aribert Rothenberger e Veit Rößner. "Psychometric Validity of the Strengths and Difficulties Questionnaire-Dysregulation Profile". Karger, 2011. https://tud.qucosa.de/id/qucosa%3A27564.
Testo completoAbstract (sommario):
Background: In many severely mentally disordered children, the clinical presentation is complicated by comorbid affective and behavioral dysregulation. Recently, a highly heritable behavioral phenotype of simultaneous deviance on the anxious/depressed, attention problems, and aggressive behavior syndrome scales has been identified on the Child Behavior Checklist Dysregulation Profile (CBCL-DP). The aim of the present pilot study was to determine an equivalent to the CBCL-DP using the Strengths and Difficulties Questionnaire (SDQ).
Sampling and Methods: We applied stepwise linear discriminant analyses and receiver operating characteristic (ROC) analysis to data from 543 consecutively referred children and adolescents, aged 5–17 years. The CBCL and the SDQ were completed by parents as part of the diagnostic routine. ICD-10 discharge diagnoses were established in consensus conferences.
Results: A combination of five SDQ items (SDQ-Dysregulation Profile, SDQ-DP) yielded the best discrimination of children with and without CBCL-DP and classified 81.0% of the subjects correctly leading to an area under the curve of 0.93. The content of the five SDQ-DP items mirrors well the mixed behavioral phenotype of anxious-depressive, aggressive and attention problems captured by the CBCL-DP. SDQ-DP status was highly correlated with CBCL-DP status and was best defined by a SDQ-DP score ≧5.
Conclusions: The psychometric properties of the SDQ-DP have been robustly tested and validated. Based on these results, clinicians may use the SDQ-DP as a useful and economical screening measure to improve the assessment, prevention, and treatment of severe dysregulation in childhood and adolescence. Future investigations should study the longitudinal stability, heritability, and genetic associations of this behavioral phenotype.Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.
36
Duncan, Andrew Paul. "The analysis and application of artificial neural networks for early warning systems in hydrology and the environment". Thesis, University of Exeter, 2014. http://hdl.handle.net/10871/17569.
Testo completoAbstract (sommario):
Artificial Neural Networks (ANNs) have been comprehensively researched, both from a computer scientific perspective and with regard to their use for predictive modelling in a wide variety of applications including hydrology and the environment. Yet their adoption for live, real-time systems remains on the whole sporadic and experimental. A plausible hypothesis is that this may be at least in part due to their treatment heretofore as “black boxes” that implicitly contain something that is unknown, or even unknowable. It is understandable that many of those responsible for delivering Early Warning Systems (EWS) might not wish to take the risk of implementing solutions perceived as containing unknown elements, despite the computational advantages that ANNs offer. This thesis therefore builds on existing efforts to open the box and develop tools and techniques that visualise, analyse and use ANN weights and biases especially from the viewpoint of neural pathways from inputs to outputs of feedforward networks. In so doing, it aims to demonstrate novel approaches to self-improving predictive model construction for both regression and classification problems. This includes Neural Pathway Strength Feature Selection (NPSFS), which uses ensembles of ANNs trained on differing subsets of data and analysis of the learnt weights to infer degrees of relevance of the input features and so build simplified models with reduced input feature sets. Case studies are carried out for prediction of flooding at multiple nodes in urban drainage networks located in three urban catchments in the UK, which demonstrate rapid, accurate prediction of flooding both for regression and classification. Predictive skill is shown to reduce beyond the time of concentration of each sewer node, when actual rainfall is used as input to the models. Further case studies model and predict statutory bacteria count exceedances for bathing water quality compliance at 5 beaches in Southwest England. An illustrative case study using a forest fires dataset from the UCI machine learning repository is also included. Results from these model ensembles generally exhibit improved performance, when compared with single ANN models. Also ensembles with reduced input feature sets, using NPSFS, demonstrate as good or improved performance when compared with the full feature set models. Conclusions are drawn about a new set of tools and techniques, including NPSFS and visualisation techniques for inspection of ANN weights, the adoption of which it is hoped may lead to improved confidence in the use of ANN for live real-time EWS applications.
37
Wang, Yuan. "Heart rate variability and respiration signals as late onset sepsis diagnostic tools in neonatal intensive care units". Thesis, Rennes 1, 2013. http://www.theses.fr/2013REN1S106/document.
Testo completoAbstract (sommario):
Le sepsis tardif, défini comme une infection systémique chez les nouveaux nés âgés de plus de 3 jours, survient chez environ 7% à 10% de tous les nouveau-nés et chez plus de 25% des nouveau-nés de très faible poids de naissance qui sont hospitalisés dans les unités de soins intensifs néonatals (USIN). Les apnées et bradycardies (AB) spontanées récurrentes et graves sont parmi les principaux indicateurs précoces cliniques de l'infection systémique chez les prématurés. L'objectif de cette thèse est de déterminer si la variabilité du rythme cardiaque (VRC), la respiration et l'analyse de leurs relations aident au diagnostic de l'infection chez les nouveaux nés prématurés par des moyens non invasifs en USIN. Par conséquent, on a effectué l'analyse Mono-Voie (MV) et Bi-Voies (BV) sur deux groupes sélectionnés de nouveau-nés prématurés: sepsis (S) vs. non-sepsis (NS). (1) Tout d'abord, on a étudié la série RR non seulement par des méthodes de distribution (moy, varn, skew, kurt, med, SpAs), par les méthodes linéaire: le domaine temporel (SD, RMSSD) et dans le domaine fréquentiel (p_VLF, p_LF, p_HF), mais aussi par les méthodes non–linéaires: la théorie du chaos (alphas, alphaF) et la théorie de l'information (AppEn, SamEn, PermEn, Regul). Pour chaque méthode, nous étudions trois tailles de fenêtre 1024/2048/4096, puis nous comparons ces méthodes afin de trouver les meilleures façons de distinguer S de NS. Les résultats montrent que les indices alphaS, alphaF et SamEn sont les paramètres optimaux pour séparer les deux populations. (2) Ensuite, la question du couplage fonctionnel entre la VRC et la respiration nasale est adressée. Des relations linéaires et non-linéaires ont été explorées. Les indices linéaires sont la corrélation (r²), l'indice de la fonction de cohérence (Cohere) et la corrélation temps-fréquence (r2t,f) , tandis que le coefficient de régression non-linéaire (h²) a été utilisé pour analyser des relations non-linéaires. Nous avons calculé les deux directions de couplage pendant l'évaluation de l'indice h2 de régression non-linéaire. Enfin, à partir de l'ensemble du processus d'analyse, il est évident que les trois indices (r2tf_rn_raw_0p2_0p4, h2_rn_raw et h2_nr_raw) sont des moyens complémentaires pour le diagnostic du sepsis de façon non-invasive chez ces patients fragiles. (3) Après, l'étude de faisabilité de la détection du sepsis en USIN est réalisée sur la base des paramètres retenus lors des études MV et BV. Nous avons montré que le test proposé, basé sur la fusion optimale des six indices ci-dessus, conduit à de bonnes performances statistiques. En conclusion, les mesures choisies lors de l'analyse des signaux en MV et BV ont une bonne répétabilité et permettent de mettre en place un test en vue du diagnostic non invasif et précoce du sepsis. Le test proposé peut être utilisé pour fournir une alarme fiable lors de la survenue d'un épisode d'AB tout en exploitant les systèmes de monitoring actuels en USINLate-onset sepsis, defined as a systemic infection in neonates older than 3 days, occurs in approximately 10% of all neonates and in more than 25% of very low birth weight infants who are hospitalized in Neonatal Intensive Care Units (NICU). Recurrent and severe spontaneous apneas and bradycardias (AB) is one of the major clinical early indicators of systemic infection in the premature infant. Various hematological and biochemical markers have been evaluated for this indication but they are invasive procedures that cannot be repeated several times. The objective of this Ph.D dissertation was to determine if heart rate variability (HRV), respiration and the analysis of their relationships help to the diagnosis of infection in premature infants via non-invasive ways in NICU. Therefore, we carried out Mono-Channel (MC) and Bi-Channel (BC) Analysis in two selected groups of premature infants: sepsis (S) vs. non-sepsis (NS). (1) Firstly, we studied the RR series not only by distribution methods (moy, varn, skew, kurt, med, SpAs), by linear methods: time domain (SD, RMSSD) and frequency domain (p_VLF, p_LF, p_HF), but also by non-linear methods: chaos theory (alphaS, alphaF) and information theory (AppEn, SamEn, PermEn, Regul). For each method, we attempt three sizes of window 1024/2048/4096, and then compare these methods in order to find the optimal ways to distinguish S from NS. The results show that alphaS, alphaF and SamEn are optimal parameters to recognize sepsis from the diagnosis of late neonatal infection in premature infants with unusual and recurrent AB. (2) The question about the functional coupling of HRV and nasal respiration is addressed. Linear and non-linear relationships have been explored. Linear indexes were correlation (r²), coherence function (Cohere) and time-frequency index (r2t,f), while a non-linear regression coefficient (h²) was used to analyze non-linear relationships. We calculated two directions during evaluate the index h2 of non-linear regression. Finally, from the entire analysis process, it is obvious that the three indexes (r2tf_rn_raw_0p2_0p4, h2_rn_raw and h2_nr_raw) were complementary ways to diagnosticate sepsis in a non-invasive way, in such delicate patients.(3) Furthermore, feasibility study is carried out on the candidate parameters selected from MC and BC respectively. We discovered that the proposed test based on optimal fusion of 6 features shows good performance with the largest Area Under Curves (AUC) and the least Probability of False Alarm (PFA). As a conclusion, we believe that the selected measures from MC and BC signal analysis have a good repeatability and accuracy to test for the diagnosis of sepsis via non-invasive NICU monitoring system, which can reliably confirm or refute the diagnosis of infection at an early stage
38
Lemos, Catarina Isabel Ferreira Miranda. "Seleção de genes diferencialmente expressos baseada em metodologia ROC (Receiver Operating Characteristic)". Master's thesis, 2017. http://hdl.handle.net/1822/56110.
Testo completoAbstract (sommario):
Dissertação de mestrado em BioinformáticaA análise da expressão genética é essencial para uma identificação da função dos genes e para a identificação destes quando relacionados com doenças. Para a realização de um estudo em larga escala de mudanças na expressão genética é necessário encontrar um método que o faça com precisão e exatidão. Desta forma, foi aqui incluída, uma análise pela tecnologia de microarrays, uma ferramenta importante no diagnóstico de doenças. A execução de um método que identificasse genes com regulação negativa e positiva e genes diferencialmente expressos simultaneamente, tornou-se, a principal motivação deste trabalho. De entre as diferentes técnicas estatísticas, a metodologia ROC (Receiver Operating Characteristic) foi a escolhida para o efeito. Quando se associa a metodologia ROC com a análise de dados de microarrays é possível ver que uma das principais aplicações é a identificação de grupos de genes associados ao desenvolvimento de qualquer patologia cancerígena. Para a análise deste último parâmetro é utilizado o arrow plot com a representação do OVL (Overlapping Coefficient) e da AUC (Area Under the Curve) para cada gene, numa experiência de microarays e comparar a sua eficácia com outros métodos existentes para o mesmo propósito. Através da análise de um conjunto de dados de pacientes afetados pelo adenocarcinoma do pâncreas foi possível identificar os genes diferencialmente expressos, sendo este o principal objetivo do trabalho em questão.
Genetic expression analysis is essential for the identification of gene function and when they are related with diseases. To perform a large-scale study of changes in gene expression it is necessary to find a method to do it with precision and accuracy. Thus, it was included here an analysis by microarray technology, an important tool in the diagnosis of diseases. The execution of a method to identify genes with negative and positive regulation and differentially expressed genes simultaneously has become the main motivation of this work. Among different statistical techniques, the receiver operating characteristic (ROC) was the chosen one. When combining the ROC methodology with microarray data analysis it is possible to see that one of the main applications is the identification of gene groups associated with the development of any kind of cancer. For the analysis of this last parameter is used the arrow plot with the overlapping coefficient (OVL) and the area under the curve (AUC) representation for each gene of a microarray experience and compare its effectiveness with other existing methods for the same purpose. Through the analysis of a set of affected patient data of pancreatic adenocarcinoma it was possible to identify differentially expressed genes, which is the main goal of this work.
39
He, Yaohua. "Nonparametric methods for receiver operating characteristic (ROC) curve analysis in genomic studies and diagnostic medicine /". 2006. http://link.library.utoronto.ca/eir/EIRdetail.cfm?Resources__ID=442590&T=F.
Testo completo
40
Shih, Ai-Ling, e 石艾伶. "An analysis of Receiver Operating Characteristic (ROC) curve on seismo-ionospheric precursors of the TEC in Taiwan". Thesis, 2016. http://ndltd.ncl.edu.tw/handle/96907108150943642907.
Testo completoAbstract (sommario):
碩士國立中央大學
太空科學研究所
104
Receiver Operating Characteristic curve (ROC curve) be used to study seismo-ionospheric precursor (SIP) in Taiwan. A median-based method together with the z test is detected the relationship between ionospheric F2-peak plasma frequency foF2 and 50 M≥5.5 earthquakes, local GPS TEC (Total Electron Content) and 50 M≥5.5 earthquakes 1994-1999, and GIM (Global Ionospheric Map) TEC 129 M≥5.5 earthquakes 1999-2014 in Taiwan. First, it is calculated that move 15-day median, upper quartile and lower quartile for create the reference range of upper bound and lower bound. The anomalies are two result that increase (positive) anomaly and decrease (negative) anomaly. In total, z-test is found that 1-4 days and 23-28 days before earthquake are negative anomaly and negative anomaly, respectively. In detail, the results of foF2 show that negative anomaly is in period of 1200-2000 LT 1-3 days before earthquake 1994-1999. However, GPS TEC shows that negative anomaly is in 1400-1600 LT 2-4 days before earthquake 1994-1999, and GIM TEC shows that negative anomaly is in 1800-2200 LT 1-3 days before earthquake 1999-2014. For positive anomaly, foF2 shows that increase in 1300-1500 LT 15-17 days, GPS TEC increase in 1200-1400 LT 24-28 days, and GIM increase in 0900-1400 LT 23-28 days. Further, different reference days (7, 15, and 30 days before and after earthquake) find that 30-days period of positive and negative anomaly. ROC curve shows that SIP is confirmed since the area under the ROC curve is positively associated with the earthquake magnitude. In addition, p-value are approximately zero mean that SIPs are effective in Taiwan.
41
Lourenço, Alexandra Sofia Costa. "Early warning system aplicado ao setor financeiro português: estudo de caso envolvendo o modelo receiver operating characteristic (ROC) curve". Master's thesis, 2017. http://hdl.handle.net/10071/15199.
Testo completoAbstract (sommario):
JEL Classification: G01, C87, E17O presente estudo é realizado com o intuito de dar um modesto contributo aos modelos Early Warning Systems (EWS), uma área em constante desenvolvimento e de crescente interesse. Em concreto, pretende-se analisar os indicadores disponíveis no sector financeiro e macroeconómico nacional, de forma a validar quais os melhores indicadores para prever uma crise financeira em Portugal. Serão analisados dados do sector financeiro e macroeconómico português, com início no 1º trimestre de 1996 e término no 4º trimestre de 2016. A seleção deste horizonte temporal teve como objetivo alcançar o máximo de dados possíveis para uma análise mais fiável. Para colocar em prática esta análise foi selecionado o modelo Receiver Operating Characteristic (ROC) curve, que permite demonstrar a relação existente entre o sinal e o ruído obtidos num teste de diagnóstico, sendo o sinal interpretado como os verdadeiros positivos (sensibilidade) e o ruído como os falsos positivos (especificidade). Através da análise ao índice Area Under Curve (AUC), que varia entre 0 e 1, classificar-se-á a qualidade da curva ROC, sendo mais eficiente quanto mais perto a AUC estiver de 1. Com a análise dos indicadores foi possível concluir que a Taxa de Variação Homóloga (TVH) do Produto Interno Bruto (PIB) (AUC de 0.956), a TVH Consumo Privado (AUC – 0.894), a TVH Deflator PIB (AUC – 0.862), TVH Formação Bruta de Capital Fixo (AUC – 0.862), o Agregado M3 (AUC – 0.859) e a TVH Importações (AUC – 0.828) são bons indicadores na previsão de crises financeiras em Portugal.
The main goal of the present Dissertation is to provide a modest contribution to the development and implementation of Early Warning Systems (EWS) models, an area of constant development and increasing interest. In particular, the Dissertation focuses on analyzing the indicators available in the Portuguese financial and macroeconomic sectors in order to validate which are the best indicators to predict a prospective financial crisis in Portugal. Data from the financial and macroeconomic Portuguese sector will be analyzed, beginning in the 1st quarter of 1996 and finishing in the 4th quarter of 2016. The selection of this large temporal horizon is due to the need to scrutinize as large a dataset as possible for a more reliable analysis. To put this analysis into practice we selected the Receiver Operating Characteristic (ROC) Curve methodology, which links the relationship between the signal and the noise obtained in a diagnostic test. The signal is interpreted as the true positives (sensitivity), while noise is interpreted as false positives (specificity). Through the analysis of the Area Under Curve (AUC) index, ranging from zero (0) to one (1). The quality of the ROC curve will be ranked accordingly, being much more effective when AUC index approaches to one (1). With the analysis of the indicators it is possible to conclude that the Annual Rate of Change (ARC) Gross domestic product (GDP) (AUC – 0.956), ARC Private consumption (AUC – 0.894), ARC GDP Deflator (AUC – 0.862), ARC Gross capital formation fixed (AUC – 0.862), M3 monetary aggregate (AUC – 0.859) and ARC Imports (AUC – 0.828) are good indicators in the forecast of financial crises in Portugal.
42
Tien, Wan-Ting, e 田婉廷. "Receiver Operating Characteristic Curve Analysis for Cure Survival Data". Thesis, 2014. http://ndltd.ncl.edu.tw/handle/07218155810473806316.
Testo completoAbstract (sommario):
碩士國立臺灣大學
數學研究所
102
Benefited from the advanced technology and medical science, more and more effective treatments for different kinds of incurable diseases have been invented. For instance, patients will not die of cancer if the radiation kills all cancer cells, so there are plenty of right-censored data at the end of the observation period. The Kaplan-Meier type estimator of survival curve shows a long and stable plateau in the tail. A characteristic of such survival data is that the survival function does not converge to zero as time goes to infinity. It is called "cure survival data". As a result, using biomarkers to discriminate uncured patients from all subjects becomes an important issue. It is related to the connection between classifications and the true status. Our primary research aim is to extend the application of true positive rate (TPR), false positive rate (FPR), and the area under receiver operating characteristic (ROC) curve (AUC) from classical survival data to cure survival data. And we will analyze the data of an angiography cohort study.
43
Araújo, Joana Margarida Rodrigues Barros de. "Avaliação do desempenho de indicadores com base na metodologia ROC (Receiver Operating Characteristic)". Master's thesis, 2015. http://hdl.handle.net/1822/38681.
Testo completoAbstract (sommario):
Dissertação de mestrado em BioinformáticaO objetivo deste estudo é avaliar e comparar o desempenho de dois indicadores de previsão de risco de mortalidade neonatal para recém-nascidos de muito baixo peso (<1500g), o CRIB (Clinical Risk Index for Babies) e o SNAPPE II (Score for Neonatal Acute Physiology-Perinatal Extension II), com recurso à metodologia ROC (Receiver Operating Characteristic). A execução prática deste estudo foi suportada com auxílio a programas estatísticos próprios para a análise da metodologia ROC, como o SPSS, ROCNPA, Comp2ROC, ROCR e caTools. Os dados que contemplam o presente estudo foram recolhidos pelas unidades de cuidados intensivos neonatais do território português entre 2010 e 2012, e enviados para o Registo Nacional de Recém-Nascidos de Muito Baixo Peso (RNMBP), que é a entidade responsável pelo armazenamento desta informação. Será aferida também a comparação e avaliação de variáveis de elevada expressão na previsão da mortalidade, que compõem os indicadores de mortalidade em estudo, sendo elas, o Peso à Nascença e a Idade Gestacional. A amostra em estudo é composta por 789 recém-nascidos de muito baixo peso, dos quais 51,3% são do género masculino. Em média os recém-nascidos em questão apresentam um peso médio ao nascimento de 1214 g ±343,1 e 29,8 ±2,5 semanas de gestação e, dos integrantes na amostra 11,3% foram declarados óbitos hospitalares. A exatidão dos indicadores de mortalidade e das variáveis foi obtida através do cálculo da AUC, área abaixo da curvaROC,queparaoCRIBfoide0,876±0,025,paraoSNAPPE-IIde0,867±0,026,seguindo-sedasvariáveisidade gestacional e o peso ao nascimento com 0,785 ±0,032 e 0,782 ±0,028, respetivamente. Com base nos resultados obtidos durante a elaboração do presente estudo, o CRIB provou ser melhor em pre dizer a mortalidade para recém-nascidos de muito baixo peso, e tem a seu favor um menor número de variáveis comparativamente ao SNAPPE-II.
The aim of this study is to evaluate and compare the performance of two scores of neonatal mortality risk prediction in very low birth weight infants (<1500g), CRIB (Clinical Risk Index for Babies) and the SNAPPE-II (Score for Neonatal Acute Physiology Perinatal Extension-II), using the ROC (Receiver Operating Characteristic) methodology. The execution of this study was supported with statistical programs for the analysis of ROC methodology, such as SPSS, ROCNPA, Comp2ROC, ROCR and caTools. The dataset used in present work was collected by the neonatal intensive care units of the Portuguese territory between 2010 and 2012, and sent to the Registo Nacional de Recém-Nascidos de Muito Baixo Peso (RNMBP), orga nization responsible by the storage of this information. Itwillbealsoassessthecomparisonandevaluationofhighexpressionvariablesinthemortalityprediction,which are part of the risk mortality scores in question, that are, the Birth Weight and Gestational Age. The dataset consists in 789 very low birth weight infants, of which 51.3% are males. The newborns in study have an average birth weight of 1214 g ±343.1g and an average gestational age of 29.8 ±2.5 weeks, and 11.3% of selected newborns were declared hospital deaths. TheaccuracyoftheriskmortalityscoresandvariableswasobtainedbycalculatingtheareaundertheROCcurve (AUC), for the CRIB was 0.876 ±0.025 and 0.867 SNAPPE-II ±0.026 following gestational age and birth weight with 0.785 ±0.032 and 0.782 ±0.028, respectively. Based on the results obtained during the elaboration of this study, CRIB proved be better to predict mortality in very low birth weight infants, and has a minor number of variables compared to SNAPPE-II.
44
Chiu, Chih-Heng, e 邱志恆. "Statistical Inferences for the Receiver Operating Characteristic Curve Analysis of An Optimal Marker". Thesis, 2010. http://ndltd.ncl.edu.tw/handle/36807823386788458545.
Testo completo
45
Yu, Suizhi. "A covariate-adjusted classification model for multiple biomarkers in disease screening and diagnosis". Diss., 2019. http://hdl.handle.net/2097/39460.
Testo completoAbstract (sommario):
Doctor of PhilosophyDepartment of Statistics
Wei-Wen Hsu
The classification methods based on a linear combination of multiple biomarkers have been widely used to improve the accuracy in disease screening and diagnosis. However, it is seldom to include covariates such as gender and age at diagnosis into these classification procedures. It is known that biomarkers or patient outcomes are often associated with some covariates in practice, therefore the inclusion of covariates may further improve the power of prediction as well as the classification accuracy. In this study, we focus on the classification methods for multiple biomarkers adjusting for covariates. First, we proposed a covariate-adjusted classification model for multiple cross-sectional biomarkers. Technically, it is a two-stage method with a parametric or non-parametric approach to combine biomarkers first, and then incorporating covariates with the use of the maximum rank correlation estimators. Specifically, these parameter coefficients associated with covariates can be estimated by maximizing the area under the receiver operating characteristic (ROC) curve. The asymptotic properties of these estimators in the model are also discussed. An intensive simulation study is conducted to evaluate the performance of this proposed method in finite sample sizes. The data of colorectal cancer and pancreatic cancer are used to illustrate the proposed methodology for multiple cross-sectional biomarkers. We further extend our classification method to longitudinal biomarkers. With the use of a natural cubic spline basis, each subject's longitudinal biomarker profile can be characterized by spline coefficients with a significant reduction in the dimension of data. Specifically, the maximum reduction can be achieved by controlling the number of knots or degrees of freedom in the spline approach, and its coefficients can be obtained by the ordinary least squares method. We consider each spline coefficient as ``biomarker'' in our previous method, then the optimal linear combination of those spline coefficients can be acquired using Stepwise method without any distributional assumption. Afterward, covariates are included by maximizing the corresponding AUC as the second stage. The proposed method is applied to the longitudinal data of Alzheimer's disease and the primary biliary cirrhosis data for illustration. We conduct a simulation study to assess the finite-sample performance of the proposed method for longitudinal biomarkers.
46
Chang, Ya-Wen, e 張雅玟. "Comparing and correction for the method of estimating three kinds of time-dependent Area under the Receiver Operating Characteristic curve". Thesis, 2016. http://ndltd.ncl.edu.tw/handle/80189855544715340582.
Testo completoAbstract (sommario):
碩士國立中央大學
統計研究所
104
In the medical diagnosis, it usually recorded the measurements for covariates of patients with returning to clinic which also called time-dependent covariates. With the property of longitudinal data, it is not suitable for using traditional area under the Receiver Operating Characteristic curve (AUC) to distinguish the biomarkers for predicting ability of diseases. According to the methods in Heagerty & Zheng (2005), van Houwelingen, Putter (2012) and Blanche, Dartigues & Jacqmin-Gadda (2013), all can estimate time-dependent AUC. Since these three kinds of methods are mainly based on the approach in Heagerty & Zheng (2005), each method computes time-dependent AUC by different ways. Hence, we focus on the method in Heagerty & Zheng (2005) and explore AUC for biomarkers via simulation and case study. Due to Heagerty & Zheng (2005) using partial likelihood function to compute AUC that needs complete covariate history and doesn’t allow for measurement error. Consequently, this thesis tries to apply joint model approach to solve the problems of partial likelihood function to obtain a better prediction.
47
Hossain, Ahmed. "Contribution to Statistical Techniques for Identifying Differentially Expressed Genes in Microarray Data". Thesis, 2011. http://hdl.handle.net/1807/29749.
Testo completoAbstract (sommario):
With the development of DNA microarray technology, scientists can now measure the expression levels of thousands of genes (features or genomic biomarkers) simultaneously in one single experiment. Robust and accurate gene selection methods are required to identify differentially expressed genes across different samples for disease diagnosis or prognosis. The problem of identifying significantly differentially expressed genes can be stated as follows: Given gene expression measurements from an experiment of two (or more)conditions, find a subset of all genes having significantly
different expression levels across these two (or more) conditions.
Analysis of genomic data is challenging due to high dimensionality of data and low sample size. Currently several mathematical and statistical methods exist to identify significantly differentially expressed genes. The methods typically focus on gene by gene analysis within a parametric hypothesis testing framework. In this study, we propose three flexible procedures for analyzing microarray data.
In the first method we propose a parametric method which is based on a flexible distribution, Generalized Logistic Distribution of Type II (GLDII), and an approximate likelihood ratio test (ALRT) is
developed. Though the method considers gene-by-gene analysis, the ALRT method with distributional assumption GLDII appears to provide a favourable fit to microarray data.
In the second method we propose a test statistic for testing whether area under receiver operating characteristic curve (AUC) for each gene is greater than 0.5 allowing different variances for each gene.
This proposed method is computationally less intensive and can identify genes that are reasonably stable with satisfactory
prediction performance. The third method is based on comparing two AUCs for a pair of genes that is designed for selecting highly
correlated genes in the microarray datasets. We propose a nonparametric procedure for selecting genes with expression levels
correlated with that of a ``seed" gene in microarray experiments.
The test proposed by DeLong et al. (1988) is the conventional nonparametric procedure for comparing correlated AUCs. It uses a
consistent variance estimator and relies on asymptotic normality of the AUC estimator. Our proposed method includes DeLong's variance estimation technique in comparing pair of genes and can identify genes with biologically sound implications.
In this thesis, we focus on the primary step in the gene selection process, namely, the ranking of genes with respect to a statistical measure of differential expression. We assess the proposed
approaches by extensive simulation studies and demonstrate the methods on real datasets. The simulation study indicates that the parametric method performs favorably well at any settings of variance, sample size and treatment effects. Importantly, the method is found less sensitive to contaminated by noise. The proposed nonparametric methods do not involve complicated formulas and do not
require advanced programming skills. Again both methods can identify a large fraction of truly differentially expressed (DE) genes,
especially if the data consists of large sample sizes or the presence of outliers. We conclude that the proposed methods offer
good choices of analytical tools to identify DE genes for further biological and clinical analysis.
48
Kolísko, Jiří. "Bankruptcy prediction models in the Czech economy: New specification using Bayesian model averaging and logistic regression on the latest data". Master's thesis, 2017. http://www.nusl.cz/ntk/nusl-367716.
Testo completoAbstract (sommario):
The main objective of our research was to develop a new bankruptcy prediction model for the Czech economy. For that purpose we used the logistic regression and 150,000 financial statements collected for the 2002-2016 period. We defined 41 explanatory variables (25 financial ratios and 16 dummy variables) and used Bayesian model averaging to select the best set of explanatory variables. The resulting model has been estimated for three prediction horizons: one, two, and three years before bankruptcy, so that we could assess the changes in the importance of explanatory variables and models' prediction accuracy. To deal with high skew in our dataset due to small number of bankrupt firms, we applied over- and under- sampling methods on the train sample (80% of data). These methods proved to enhance our classifier's accuracy for all specifications and periods. The accuracy of our models has been evaluated by Receiver operating characteristics curves, Sensitivity-Specificity curves, and Precision-Recall curves. In comparison with models examined on similar data, our model performed very well. In addition, we have selected the most powerful predictors for short- and long-term horizons, which is potentially of high relevance for practice. JEL Classification C11, C51, C53, G33, M21 Keywords Bankruptcy...
49
"Diagnostic Utility of the Culture-Language Interpretive Matrix for the WISC-IV Among Referred Students". Doctoral diss., 2012. http://hdl.handle.net/2286/R.I.15045.
Testo completoAbstract (sommario):
abstract: The Culture-Language Interpretive Matrix (C-LIM) is a new tool hypothesized to help practitioners accurately determine whether students who are administered an IQ test are culturally and linguistically different from the normative comparison group (i.e., different) or culturally and linguistically similar to the normative comparison group and possibly have Specific Learning Disabilities (SLD) or other neurocognitive disabilities (i.e., disordered). Diagnostic utility statistics were used to test the ability of the Wechsler Intelligence Scales for Children-Fourth Edition (WISC-IV) C-LIM to accurately identify students from a referred sample of English language learners (Ells) (n = 86) for whom Spanish was the primary language spoken at home and a sample of students from the WISC-IV normative sample (n = 2,033) as either culturally and linguistically different from the WISC-IV normative sample or culturally and linguistically similar to the WISC-IV normative sample. WISC-IV scores from three paired comparison groups were analyzed using the Receiver Operating Characteristic (ROC) curve: (a) Ells with SLD and the WISC-IV normative sample, (b) Ells without SLD and the WISC-IV normative sample, and (c) Ells with SLD and Ells without SLD. Results of the ROC yielded Area Under the Curve (AUC) values that ranged between 0.51 and 0.53 for the comparison between Ells with SLD and the WISC-IV normative sample, AUC values that ranged between 0.48 and 0.53 for the comparison between Ells without SLD and the WISC-IV normative sample, and AUC values that ranged between 0.49 and 0.55 for the comparison between Ells with SLD and Ells without SLD. These values indicate that the C-LIM has low diagnostic accuracy in terms of differentiating between a sample of Ells and the WISC-IV normative sample. Current available evidence does not support use of the C-LIM in applied practice at this time.Dissertation/Thesis
Ph.D. Educational Psychology 2012
50
Mourão, Maria Filipa Torres Gonçalves Flores. "Aplicação da metodologia ROC na avaliação de desempenho de índices de gravidade clínica em unidades de neonatologia de Portugal". Doctoral thesis, 2015. http://hdl.handle.net/1822/40535.
Testo completoAbstract (sommario):
Tese de Doutoramento em Engenharia Industrial e de SistemasOs cuidados intensivos pediátricos em Portugal são prestados por uma diversidade de Unidades de Cuidados Intensivos interessando neste estudo, em particular, as unidades que prestam cuidados a recém nascidos de muito baixo peso (<1500 g) e/ou com menos de 32 semanas de gestação. Atualmente, são usadas escalas/índices para medir a gravidade clínica de recém-nascidos, sendo as mais utilizadas no território nacional a Clinical Risk Index for Babies (CRIB) e a Score for Neonatal Acute Physiology II (SNAPPE II). Cada unidade procede a uma recolha individualizada dos dados referentes à sua atividade e que são enviados para o Registo Nacional de Recém-Nascidos de Muito Baixo Peso (RNMBP), que é a entidade responsável pelo armazenamento desta informação. Os dados que integram o presente estudo foram recolhidos pelas unidades de cuidados intensivos neonatais do território português (Continente e Ilhas) entre 2010 e 2012, e o objetivo passa pela avaliação e comparação do desempenho desses dois indicadores (CRIB e SNAPPE II), no que respeita à sua capacidade preditiva da mortalidade neonatal, com recurso à metodologia ROC (Receiver Operating Characteristic), quer a nível do território nacional (Continente e Ilhas) quer a nível diferenciado pela Nomenclatura das Unidades Territoriais para fins Estatísticos (NUTS II). Segundo essa Nomenclatura, consideram-se as regiões: Norte (Viana do Castelo, Braga, Porto, Vila Real e Bragança), Centro (Coimbra, Castelo Branco, Leiria, Viseu, Aveiro e Guarda), Lisboa/Vale do Tejo (Lisboa e Setúbal), Alentejo (Évora, Santarém, Beja e Portalegre), Algarve (Faro) e Ilhas (Açores e Madeira). É avaliada também a influência do sexo do recém-nascido e da idade materna, no poder discriminante das duas escalas, como possíveis covariáveis com expressão na previsão da mortalidade. Neste trabalho aplica-se a análise ROC como metodologia base, ajustando-se curvas ROC empíricas, alisadas (por aplicação do estimador de núcleo) e condicionadas a covariáveis, quer pelo método induzido quer aplicando modelos de regressão linear ROC-GLM, tendo sido obtidas as respetivas medidas de precisão (área abaixo da curva ROC e erro padrão). Para a amostra em estudo, quando considerado todo o território nacional, a escala CRIB provou ser melhor a predizer a mortalidade para recém-nascidos de muito baixo peso, e tem a seu favor um menor número de variáveis comparativamente ao SNAPPE II. A comparação entre a capacidade preditiva das duas escalas, quando utilizado o estimador do núcleo para a obtenção das curvas ROC e as correspondentes curvas ROC empíricas, mostram que as últimas apresentam melhor desempenho. A introdução das covariáveis, sexo do recém-nascido e idade materna, no modelo obtido pelo método induzido mostra que nem a escala CRIB nem a escala SNAPPE II, a nível global, apresentam um desempenho diferenciado na previsão da mortalidade (software R). Considerando que uma relação linear existe entre cada uma das escalas e as covariáveis sexo do recém-nascido, idade da mãe e combinando a informação das duas, utilizando o software STATA, verificou-se que a capacidade discriminante e preditiva da escala CRIB é influenciada pela idade da mãe enquanto a da escala SNAPPE II não se altera sob alguma das possibilidades. A combinação das duas covariáveis faz aumentar o poder discriminante dessa escala. Avaliou-se como contribuem as Unidades de Neonatologia que integram os centros hospitalares das regiões classificadas pela Nomenclatura NUTS II, na capacidade discriminante e preditiva das duas escalas. Na região Norte e na região Lisboa/Vale do Tejo a escala CRIB provou ser melhor na previsão da mortalidade. Para as restantes regiões, o desempenho das escalas é idêntico na previsão da mortalidade. Nas UCIN's das Ilhas, a escala CRIB, quando comparada com a SNAPPE II, provou ter um melhor desempenho na avaliação da mortalidade para recém-nascidos do sexo feminino, enquanto que a introdução da idade da mãe provou que, com base nos valores estimados, a CRIB, para recém-nascidos cujas mães têm idade igual ou superior a 35 anos, apresenta um melhor desempenho nas UCIN's da região Norte e do Algarve. A execução prática deste estudo foi suportada com auxílio a programas estatísticos próprios para a análise ROC, como o SPSS, ROCNPA, ROCR e STATA.
Pediatric intensive care in Portugal are provided by a variety of Intensive Care Units. In this study, in particular, the interest lies on units providing care to babies of very low birth weight (<1500 g) and/or less than 32 weeks gestation. Currently, scores/indexes are used to measure the clinical severity of newborns. The most used in Portugal are the Clinical Risk Index for Babies (CRIB) and the Score for Neonatal Acute Physiology II (SNAPPE II). Each unit carries out an individualized collection of data on its activity and that are sent to the National Register of Very Low Birth Weight Newborn (VLBWN), which is responsible for storing this information. The data that are part of the present study were collected by the neonatal intensive care units of the Portuguese territory (mainland and islands) between 2010 and 2012, and the goal involves the evaluation and comparison of the performance of these two indicators (CRIB and SNAPPE II) as regards its predictive ability of neonatal mortality, using the ROC (Receiver Operating Characteristic) methodology. This analysis was performed at the level of mainland Portugal and for the Nomenclature of Territorial Units for Statistics (NUTS II). According to this nomenclature, the regions considered are: Northern (Viana do Castelo, Braga, Porto, Vila Real and Bragança), Center (Coimbra, Castelo Branco, Leiria, Viseu, Aveiro and Guarda), Lisbon/Tejo's Valley (Lisbon and Setúbal), Alentejo (Évora, Santarém, Beja and Portalegre), Algarve (Faro) and Islands (Azores and Madeira). It is also evaluated the influence of the newborn sex and maternal age, on the discriminating power of the two scores as potential covariates with expression in predicting mortality. In this work, the ROC analysis is used as a base methodology, to adjust empirical ROC curves, smoothed ROC curves (using kernel estimator) and for adjusting conditioned ROC curves. For the latest, induced method and models of ROC-GLM regression were applied. For the sample under study, when considering the national territory, the CRIB scale proved better to predict mortality for newborns with very low weight, and has in its favor a smaller number of variables compared to SNAPPE II. Compared the smoothed estimator of the ROC curve with the empirical estimator, the latter shows up more predictive capacity, then better performance. The introduction of covariates (newborn sex and maternal age) when used induced method (software R), shows that neither the CRIB score nor the SNAPPE II, have a differentiated performance in predicting mortality. When a linear relationship between each scale and the covariates is considered (software STATA) it was found that the discriminatory and predictive capacity of the CRIB score is influenced by maternal age while the SNAPPE II scale does not change under any of the possibilities. The combination of the two covariates increases the discriminating power of CRIB score. It was evaluated as contributing the neonatology units that integrate the hospital centers of the regions classified by the nomenclature NUTS II, in discriminant and predictive capacity of the two scales. In North and Lisbon/Tejo's Valley regions the CRIB score proved to be better in predicting mortality. For all other regions, the performance of the two scales in predicting mortality is identical. In the NICU's Islands, the CRIB scale compared with SNAPPE II, proved to perform better in the evaluation of mortality for female newborns; the introduction of the mother's age proved that CRIB score, for newborns whose mothers are aged less than 35 years, presents a better performance in the NICU's of northern and Algarve regions. The practical implementation of this study was supported by statistical programs for ROC analysis, such as SPSS, ROCNPA, ROCR and STATA.