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Relevant bibliographies by topics / ROC (receiver operating characteristic) curve

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Academic literature on the topic 'ROC (receiver operating characteristic) curve'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "ROC (receiver operating characteristic) curve"

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Yang, Shengping, and Gilbert Berdine. "The receiver operating characteristic (ROC) curve." Southwest Respiratory and Critical Care Chronicles 5, no. 19 (2017): 34. http://dx.doi.org/10.12746/swrccc.v5i19.391.

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Fan, Jerome, Suneel Upadhye, and Andrew Worster. "Understanding receiver operating characteristic (ROC) curves." CJEM 8, no. 01 (2006): 19–20. http://dx.doi.org/10.1017/s1481803500013336.

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In this issue of the Journal, Auer and colleagues conclude that serum levels of neuron-specific enolase (NSE), a biochemical marker of ischemic brain injury, may have clinical utility for the prediction of survival to hospital discharge in patients experiencing the return of spontaneous circulation following at least 5 minutes of cardiopulmonary resuscitation. The authors used a receiver operating characteristic (ROC) curve to illustrate and evaluate the diagnostic (prognostic) performance of NSE. We explain ROC curve analysis in the following paragraphs.

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Pendrill, Leslie R., Jeanette Melin, Anne Stavelin, and Gunnar Nordin. "Modernising Receiver Operating Characteristic (ROC) Curves." Algorithms 16, no. 5 (2023): 253. http://dx.doi.org/10.3390/a16050253.

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The justification for making a measurement can be sought in asking what decisions are based on measurement, such as in assessing the compliance of a quality characteristic of an entity in relation to a specification limit, SL. The relative performance of testing devices and classification algorithms used in assessing compliance is often evaluated using the venerable and ever popular receiver operating characteristic (ROC). However, the ROC tool has potentially all the limitations of classic test theory (CTT) such as the non-linearity, effects of ordinality and confounding task difficulty and i

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Nahm, Francis Sahngun. "Receiver operating characteristic curve: overview and practical use for clinicians." Korean Journal of Anesthesiology 75, no. 1 (2022): 25–36. http://dx.doi.org/10.4097/kja.21209.

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Using diagnostic testing to determine the presence or absence of a disease is essential in clinical practice. In many cases, test results are obtained as continuous values and require a process of conversion and interpretation and into a dichotomous form to determine the presence of a disease. The primary method used for this process is the receiver operating characteristic (ROC) curve. The ROC curve is used to assess the overall diagnostic performance of a test and to compare the performance of two or more diagnostic tests. It is also used to select an optimal cut-off value for determining th

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Kumar, Rajeev, and Abhaya Indrayan. "Receiver operating characteristic (ROC) curve for medical researchers." Indian Pediatrics 48, no. 4 (2011): 277–87. http://dx.doi.org/10.1007/s13312-011-0055-4.

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Park, Seong Ho, Jin Mo Goo, and Chan-Hee Jo. "Receiver Operating Characteristic (ROC) Curve: Practical Review for Radiologists." Korean Journal of Radiology 5, no. 1 (2004): 11. http://dx.doi.org/10.3348/kjr.2004.5.1.11.

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Kawada, Tomoyuki. "Sample Size in Receiver-Operating Characteristic (ROC) Curve Analysis." Circulation Journal 76, no. 3 (2012): 768. http://dx.doi.org/10.1253/circj.cj-11-1408.

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Yoshinaga, Keiichiro, Kazumasa Tsukamoto, and Nagara Tamaki. "Sample Size in Receiver-Operating Characteristic (ROC) Curve Analysis." Circulation Journal 76, no. 3 (2012): 769. http://dx.doi.org/10.1253/circj.cj-11-1503.

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Cook, Jonathan A., and Ashish Rajbhandari. "Heckroccurve: ROC Curves for Selected Samples." Stata Journal: Promoting communications on statistics and Stata 18, no. 1 (2018): 174–83. http://dx.doi.org/10.1177/1536867x1801800110.

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Receiver operating characteristic (ROC) curves can be misleading when they are constructed with selected samples. In this article, we describe heckroccurve, which implements a recently developed procedure for plotting ROC curves with selected samples. The command estimates the area under the ROC curve and a graphical display of the curve. A variety of plot options are available, including the ability to add confidence bands to the plot.

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Shankar, P. M. "Parametric modeling of receiver operating characteristics curves." Model Assisted Statistics and Applications 19, no. 2 (2024): 211–21. http://dx.doi.org/10.3233/mas-231475.

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Receiver operating characteristics (ROC) curves play a pivotal role in the analyses of data collected in applications involving machine vision, machine learning and clinical diagnostics. The importance of ROC curves lies in the fact that all decision-making strategies rely on the interpretations of the curves and features extracted from them. Such analyses become simple and straightforward if it is possible to have a statistical fit for the empirical ROC curve. A methodology is developed and demonstrated to obtain a parametric fit for the ROC curves using multiple tools in statistics such as c

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Dissertations / Theses on the topic "ROC (receiver operating characteristic) curve"

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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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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.

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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 ot

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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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池田, 充., Takeo Ishigaki, Mitsuru Ikeda, 一信山内, and 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.

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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

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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.

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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.

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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, riesc

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Sun, Fangfang. "Semi-parametric inference for the partial area under the ROC curve." unrestricted, 2008. http://etd.gsu.edu/theses/available/etd-11192008-113213/.

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Thesis (M.S.)--Georgia State University, 2008.<br>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).

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Books on the topic "ROC (receiver operating characteristic) curve"

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J, Hand D., ed. ROC curves for continuous data. Chapman & Hall/CRC, 2009.

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Matheja, Roswitha. Vergleichende Bildgütenuntersuchungen zweier Film-Folien-Systeme mit Weichstrahlraster sowie eines Film-Folien-Systems ohne Raster zum Einsatz für die Mammographie mittels receiver-operating-characteristic (ROC)-Analyse. [s.n.], 1985.

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He, Yaohua. Nonparametric methods for receiver operating characteristic (ROC) curve analysis in genomic studies and diagnostic medicine. 2006.

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Zou, Kelly H., Aiyi Liu, Andriy I. Bandos, Lucila Ohno-Machado, and Howard E. Rockette. Statistical Evaluation of Diagnostic Performance: Topics in ROC Analysis. Taylor & Francis Group, 2016.

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Zou, Kelly H. Statistical Evaluation of Diagnostic Performance: Topics in Roc Analysis. Taylor & Francis Group, 2011.

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Zou, Kelly H., Aiyi Liu, Andriy I. Bandos, Lucila Ohno-Machado, and Howard E. Rockette. Statistical Evaluation of Diagnostic Performance: Topics in ROC Analysis. Taylor & Francis Group, 2016.

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Statistical evaluation of diagnostic performance: Topics in ROC analysis. Taylor & Francis, 2012.

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Peacock, Janet L., Sally M. Kerry, and Raymond R. Balise. Single group studies. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198779100.003.0006.

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Chapter 6 discusses single group studies, and covers prevalence, how to present results, screening studies, calculating, and presenting sensitivity and specificity. It discusses how to deal with calculations with a rare condition where the numbers are small. Finally, it discusses the use of receiver operating characteristic (ROC) curves. The chapter includes analyses using Stata, SAS, SPSS, and R.

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Signal detection theory and ROC analysis in psychology and diagnostics: Collected papers. L. Erlbaum Associates, 1996.

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Observer Performance Methods for Diagnostic Imaging: Foundations, Modeling, and Applications with R-Based Examples. Taylor & Francis Group, 2017.

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Book chapters on the topic "ROC (receiver operating characteristic) curve"

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Melo, Francisco. "Receiver Operating Characteristic (ROC) Curve." In Encyclopedia of Systems Biology. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_242.

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Srinivasan, Anand, and Archana Mishra. "Receiver Operating Characteristic (ROC) Curve Analysis for Diagnostic Studies." In R for Basic Biostatistics in Medical Research. Springer Nature Singapore, 2024. https://doi.org/10.1007/978-981-97-6980-3_12.

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Marcus, Pamela M. "Performance Measures." In Assessment of Cancer Screening. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94577-0_3.

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AbstractPerformance measures reflect the link between cancer screening test results and cancer diagnoses. They measure the ability of cancer screening to lead to detection of cancer, and provide no evidence as to screening’s ability to reduce mortality. Performance measures are rarely considered sufficient evidence to implement cancer screening for the first time, though they have driven dissemination of tests that are thought to represent upgrades of established cancer screening tests. Chapter 3 presents the six key performance measures: sensitivity, specificity, positive predictive value, ne

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Mas, J. F. "Receiver Operating Characteristic (ROC) Analysis." In Geomatic Approaches for Modeling Land Change Scenarios. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60801-3_30.

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Xiuyan, Guo. "Receiver Operating Characteristic Curve." In The ECPH Encyclopedia of Psychology. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-6000-2_814-1.

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Xiuyan, Guo. "Receiver Operating Characteristic Curve." In The ECPH Encyclopedia of Psychology. Springer Nature Singapore, 2024. https://doi.org/10.1007/978-981-97-7874-4_814.

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Inkinen, S. I., A. O. Kotiaho, M. Hanni, M. T. Nieminen, and M. A. K. Brix. "Computed Tomography Artefact Detection Using Deep Learning—Towards Automated Quality Assurance." In Communications in Computer and Information Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-59091-7_2.

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AbstractImage artefacts in computed tomography (CT) limit the diagnostic quality of the images. The objective of this proof-of-concept study was to apply deep learning (DL) for automated CT artefact classification. Openly available Head CT data from Johns Hopkins University was used. Three common artefacts (patient movement, beam hardening, and ring artefacts (RAs)) and artefact free images were simulated using 2D axial slices. Simulated data were split into a training set (Ntrain = 1040 × 4(4160)), two validation sets (Nval1 = 130 × 4(520) and Nval2 = 130 × 4(520)), and a separate test set (N

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Ishihara, Hideyuki, Fumiaki Oka, Takuma Nishimoto, Masatoshi Yamane, Kazutaka Sugimoto, and Hirokazu Sadahiro. "ADC Threshold Indicating the Ischemic Region for Predicting Efficacy in Thrombectomy." In Acta Neurochirurgica Supplement. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-89844-0_16.

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Abstract Purpose: The effectiveness of endovascular thrombectomy (EVT) has been proven in patients with large cerebral infarction. However, the size of the ischemic region before treatment is a significant factor in the outcome, and the optimal method for the evaluation of this region is uncertain. The goal of this study was to investigate apparent diffusion coefficient (ADC) values as a basis for an assessment of the ischemic region before treatment. Methods: A retrospective study was performed in 48 consecutive patients who underwent EVT for acute large vessel occlusion (LVO) with Alberta St

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Nockemann, C., G. R. Tillack, H. Wessel, H. Heidt, and V. Konchina. "Receiver Operating Characteristic (ROC) in Nondestructive Inspection." In Advances in Signal Processing for Nondestructive Evaluation of Materials. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1056-3_2.

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Wijaya, I. Putu Krishna, Peeranan Towashiraporn, Anish Joshi, Susantha Jayasinghe, Anggraini Dewi, and Md Nurul Alam. "Climate Change-Induced Regional Landslide Hazard and Exposure Assessment for Aiding Climate Resilient Road Infrastructure Planning: A Case Study in Bagmati and Madhesh Provinces, Nepal." In Progress in Landslide Research and Technology, Volume 1 Issue 1, 2022. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-16898-7_12.

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AbstractNepal’s hilly and mountainous regions are highly susceptible to landslides triggered by extreme precipitations. The prevalence of such landslides has increased due to climate change-induced extreme hydro-meteorological conditions. These recurring landslides have significantly impacted the road transport infrastructure, which is the economic lifeline for cities and socio-economic mobility of rural communities in the hilly and mountainous regions of the country. This study modelled extreme rainfall scenarios for the current 1976–2005 baseline and future horizons of 2030, 2050, and 2080 t

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Conference papers on the topic "ROC (receiver operating characteristic) curve"

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Namdar, Khashayar, and Farzad Khalvati. "Advanced Receiver Operating Characteristic Curve Analysis to Identify Outliers in Binary Machine Learning Classifications for Precision Medicine." In 2024 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI). IEEE, 2024. https://doi.org/10.1109/bhi62660.2024.10913597.

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Wu, Tao, Haibin Huang, Guangwei Du, and Yiyong Sun. "A novel partial area index of receiver operating characteristic (ROC) curve." In Medical Imaging, edited by Berkman Sahiner and David J. Manning. SPIE, 2008. http://dx.doi.org/10.1117/12.769888.

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Trickey, Stephen, Mark Seaver, and Jon Nichols. "Quantification of damage detection schemes using receiver operating characteristic (ROC) curves." In The 14th International Symposium on: Smart Structures and Materials & Nondestructive Evaluation and Health Monitoring, edited by H. Felix Wu, Aaron A. Diaz, and Peter J. Shull. SPIE, 2007. http://dx.doi.org/10.1117/12.715210.

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Swensson, Richard G., Jill L. King, Walter F. Good, and David Gur. "Using a constrained formulation based on probability summation to fit receiver operating characteristic (ROC) curves." In Medical Imaging 2000, edited by Elizabeth A. Krupinski. SPIE, 2000. http://dx.doi.org/10.1117/12.383102.

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G, Kavitha, Deepa M, Mishal A, Shahira S, and Sharmila Devi S. "Human Pharyngeal Neoplasm Detection using Artificial Intelligence." In International Conference on Modern Trends in Engineering and Management (ICMTEM-24). International Journal of Advanced Trends in Engineering and Management, 2024. http://dx.doi.org/10.59544/bveq1259/icmtem24p6.

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The pharynx plays a most significant role in serving both the body’s air food passageway systems. Pharyngeal neoplasm happens when tissues in the throat grow and spread abnormally, destroying healthy cells. So, pharyngeal neoplasm detection plays a vital role in timely and accurate diagnostic methods for improved patient result outcomes. In this project, we propose a machine learning based classification system for the automated detection of pharyngeal neoplasm using medical imaging data. A convolution neural network (CNN) architecture was designed and trained on the labelled dataset for class

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Amokun, R., O. Arowolo, and J. Eke. "Comparative Analysis of Machine Learning Algorithms for Heart Disease Prediction Using CDC and BRFSS Data: A Focus on Oversampling and Ensemble Techniques." In International Conference on Artificial Intelligence and Robotics. Machine Intelligence Research Group (MIRG), 2024. https://doi.org/10.52968/15069725.

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This work studies machine learning methods to predict heart disease based on data obtained from the CDC via the Behavioral Risk Factor Surveillance System. Accordingly, it compared various models, including Logistic Regression and Random Forest models, which can be further tuned for better outcomes in heart disease treatment and prevention. With a view to handling the class imbalance problem in heart disease classification, the SMOTE technique was applied, and model performance was evaluated on metrics such as Accuracy and Precision, among others. The high marks the F Score and ROC Area under

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Davison, Craig R., and Chris Drummond. "Application of Cost Matrices and Cost Curves to Enhance Diagnostic Health Management Metrics for Gas Turbine Engines." In ASME Turbo Expo 2009: Power for Land, Sea, and Air. ASMEDC, 2009. http://dx.doi.org/10.1115/gt2009-59630.

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Statistically based metrics for gas turbine engine diagnostic systems are required to evaluate competing products fairly and to establish a convincing business case. Diagnostic algorithm validation often includes engine testing with implanted faults. The implantation rate is rarely, if ever, representative of the true fault occurrence rate. A technique is presented to convert a confusion matrix with a non-representative fault distribution to one representative of the expected distribution. The small sample size associated with fault implantation studies requires a confidence interval on the re

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Souza, Vitor Pires Silva e., Deborah Silva Alves Fernandes, Silvana L. V. dos Santos, and Márcio Giovane Cunha Fernandes. "Previsão de infecção relacionada à assistência à saúde em pacientes adultos de UTI utilizando ferramentas de inteligência artificial." In Simpósio Brasileiro de Computação Aplicada à Saúde. Sociedade Brasileira de Computação - SBC, 2024. http://dx.doi.org/10.5753/sbcas.2024.2778.

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Este artigo explora o uso de técnicas de inteligência artificial para prever Infecções Relacionadas à Assistência à Saúde (IRAS). O estudo, baseado em dados de um Hospital Escola de referência coletados entre janeiro e agosto de 2021, investiga quais algoritmos de aprendizado de máquina são mais eficazes para prever IRAS. Foram utilizados algoritmos de classificação, como Random Forest, Decision Tree, Gradient Boosting, Adaboost e XGboost. A métrica da área sob a curva ROC (Receiver Operating Characteristic) e StratifiedKFold foram utilizados para medir o desempenho dos modelos. Os resultados

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Velásquez Pérez, Torcoroma. "Prácticas pedagógicas emergentes." In Nuevas realidades para la educación en ingeniería: currículo, tecnología, medio ambiente y desarrollo. Asociacion Colombiana de Facultades de Ingeniería - ACOFI, 2022. http://dx.doi.org/10.26507/paper.2283.

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Los modelos educativos en la actualidad han perdido vigencia, más cuando la educación se ha enfrentado a una transición de la educación presencial a la educación mediada por tecnologías, para la cual nadie estaba preparado; las secuelas de la pandemia del COVID-19 (SARS-CoV-2), han dejado huellas imborrables en el devenir histórico de la humanidad; los sistemas han tenido que re-inventarse sobre la marcha y ajustar a nuevas estructuras para dar continuidad a los procesos de formación y capacitación; de allí emerge el objetivo del presente aporte: generar un compendio teórico – práctico de peda

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Bonadio, Renata Rodrigues da Cunha Colombo, Monique Tavares, Jose Bines, et al. "Prediction of pathologic complete response to chemoimmunotherapy in triple-negative breast cancer using tumor-infiltrating lymphocytes: exploiting cutoff values." In Brazilian Breast Cancer Symposium 2024. Mastology, 2024. http://dx.doi.org/10.29289/259453942024v34s1052.

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Objective: Triple-negative breast cancer (TNBC) prognosis is significantly influenced by tumor-infiltrating lymphocytes (TILs), but the lack of validated cutoff values limits their clinical applicability. This study aimed to assess TILs as predictors of pathologic complete response (pCR) within the Neo-Real study, a multicenter, real-world data investigation on neoadjuvant pembrolizumab plus chemotherapy (P+CT) for TNBC. Methodology: TILs were evaluated using the standardized methodology of the International TILs Working Group. Logistic regression and receiver operating characteristic (ROC) cu

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Reports on the topic "ROC (receiver operating characteristic) curve"

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Sullivan, Keith M. Global Receiver Operating Characteristic (ROC) Curves for Three Network Topologies. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada636523.

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Candy, J., and E. Breitfeller. Receiver Operating Characteristic (ROC) Curves: An Analysis Tool for Detection Performance. Office of Scientific and Technical Information (OSTI), 2013. http://dx.doi.org/10.2172/1093414.

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Qin, Ling, Qiyu Liu, Hui Wang, and Lipeng Sun. Accuracy of ultrasound in distinguishing pathology of malignant thyroid diseases: A protocol for systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2021. http://dx.doi.org/10.37766/inplasy2021.12.0072.

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Review question / Objective: This meta-analysis aimed to determine the accuracy of ultrasound in distinguishing pathology of malignant thyroid diseases. Eligibility criteria: Type of study. This study will only include high quality clinical cohort or case control studies. Type of patients. The patients should be those who had undergone breast diseases. Intervention and comparison. This study compares AI with pathology for diagnosing breast diseases. Type of outcomes. The primary outcomes include sensitivity, specificity, positive and negative likelihood ratio, diagnostic odds ratio, and the ar

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Tayeb, Shahab. Taming the Data in the Internet of Vehicles. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2014.

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As an emerging field, the Internet of Vehicles (IoV) has a myriad of security vulnerabilities that must be addressed to protect system integrity. To stay ahead of novel attacks, cybersecurity professionals are developing new software and systems using machine learning techniques. Neural network architectures improve such systems, including Intrusion Detection System (IDSs), by implementing anomaly detection, which differentiates benign data packets from malicious ones. For an IDS to best predict anomalies, the model is trained on data that is typically pre-processed through normalization and f

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Hamlin, Alexandra, Erik Kobylarz, James Lever, Susan Taylor, and Laura Ray. Assessing the feasibility of detecting epileptic seizures using non-cerebral sensor. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42562.

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This paper investigates the feasibility of using non-cerebral, time-series data to detect epileptic seizures. Data were recorded from fifteen patients (7 male, 5 female, 3 not noted, mean age 36.17 yrs), five of whom had a total of seven seizures. Patients were monitored in an inpatient setting using standard video electroencephalography (vEEG), while also wearing sensors monitoring electrocardiography, electrodermal activity, electromyography, accelerometry, and audio signals (vocalizations). A systematic and detailed study was conducted to identify the sensors and the features derived from t

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Jittapiromsak, Nutchawan. Value of Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Determining the Plasma Epstein-Barr Virus Status and Staging of Nasopharyngeal Carcinoma. Faculty of Medicine, Chulalongkorn University, 2019. https://doi.org/10.58837/chula.res.2019.9.

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Abstract:

Objective: To determine the associations between dynamic-contrast enhanced (DCE) magnetic resonance imaging (MRI) parameters and plasma Epstein-Barr virus (EBV) DNA status and nasopharyngeal carcinoma (NPC) stages. Methods: We prospectively studied the DCE MRI results of 47 patients with newly diagnosed NPC and a known pre-treatment plasma EBV DNA level. Regions of interest (ROIs) were drawn at primary tumors, and DCE MRI parameters, including mean and max values of Ktrans, Kep Ve, and Vp, were recorded. Spearman’s rank correlation was used to identify significant associations between DCE MRI

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