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Journal articles on the topic 'Optimal scoring'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 February 2022

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1

Ramsay, James, Marie Wiberg, and Juan Li. "Full Information Optimal Scoring." Journal of Educational and Behavioral Statistics 45, no. 3 (2019): 297–315. http://dx.doi.org/10.3102/1076998619885636.

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Ramsay and Wiberg used a new version of item response theory that represents test performance over nonnegative closed intervals such as [0, 100] or [0, n] and demonstrated that optimal scoring of binary test data yielded substantial improvements in point-wise root-mean-squared error and bias over number right or sum scoring. We extend these results by showing that optimal scoring of the full information in option choices produces about as much further improvement in these measures of score performance as was achieved by going from sum scoring to optimal binary scoring.

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Konigsberg, Lyle W., Susan R. Frankenberg, and Helen M. Liversidge. "Optimal trait scoring for age estimation." American Journal of Physical Anthropology 159, no. 4 (2015): 557–76. http://dx.doi.org/10.1002/ajpa.22914.

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3

Hastie, Trevor, Robert Tibshirani, and Andreas Buja. "Flexible Discriminant Analysis by Optimal Scoring." Journal of the American Statistical Association 89, no. 428 (1994): 1255–70. http://dx.doi.org/10.1080/01621459.1994.10476866.

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4

Beling, P., Z. Covaliu, and R. M. Oliver. "Optimal scoring cutoff policies and efficient frontiers." Journal of the Operational Research Society 56, no. 9 (2005): 1016–29. http://dx.doi.org/10.1057/palgrave.jors.2602021.

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5

Wang, Tao, and Lixing Zhu. "Sparse sufficient dimension reduction using optimal scoring." Computational Statistics & Data Analysis 57, no. 1 (2013): 223–32. http://dx.doi.org/10.1016/j.csda.2012.06.015.

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6

Clémençon, Stéphan, and Nicolas Vayatis. "Overlaying Classifiers: A Practical Approach to Optimal Scoring." Constructive Approximation 32, no. 3 (2010): 619–48. http://dx.doi.org/10.1007/s00365-010-9084-9.

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Feldbacher-Escamilla, Christian J., and Gerhard Schurz. "Optimal probability aggregation based on generalized brier scoring." Annals of Mathematics and Artificial Intelligence 88, no. 7 (2019): 717–34. http://dx.doi.org/10.1007/s10472-019-09648-4.

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Nishimura, Takeshi. "Optimal design of scoring auctions with multidimensional quality." Review of Economic Design 19, no. 2 (2015): 117–43. http://dx.doi.org/10.1007/s10058-015-0169-6.

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9

Camilli, Gregory. "IRT Scoring and Test Blueprint Fidelity." Applied Psychological Measurement 42, no. 5 (2018): 393–400. http://dx.doi.org/10.1177/0146621618754897.

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This article focuses on the topic of how item response theory (IRT) scoring models reflect the intended content allocation in a set of test specifications or test blueprint. Although either an adaptive or linear assessment can be built to reflect a set of design specifications, the method of scoring is also a critical step. Standard IRT models employ a set of optimal scoring weights, and these weights depend on item parameters in the two-parameter logistic (2PL) and three-parameter logistic (3PL) models. The current article is an investigation of whether the scoring models reflect an intended set of weights defined as the proportion of item falling into each cell of the test blueprint. The 3PL model is of special interest because the optimal scoring weights depend on ability. Thus, the concern arises that for examinees of low ability, the intended weights are implicitly altered.

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Tiemensma, Jitske, Sarah Depaoli, and John M. Felt. "Using subscales when scoring the Cushing's quality of life questionnaire." European Journal of Endocrinology 174, no. 1 (2016): 33–40. http://dx.doi.org/10.1530/eje-15-0640.

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ContextPatients in long-term remission of Cushing's syndrome (CS) commonly report impaired quality of life (QoL). The CushingQoL questionnaire is a disease-specific QoL questionnaire for patients diagnosed with CS. The developers of the CushingQoL recommend using a global (total) score to assess QoL. However, the global score does not capture all aspects of QoL as outlined by the World Health Organization (WHO).ObjectiveThe aim of the study was to compare the performance of different scoring options to determine the optimal method for the CushingQoL.Design and patientsPatients in remission from CS (n=341) were recruited from the Cushing's Syndrome Research Foundation's email listserv and Facebook page, and asked to complete the CushingQoL and a short demographics survey.ResultsUsing an exploratory analysis, adequate model fit was obtained for the global score, as well as a 2-subscale (psychosocial issues and physical problems) scoring solution. Confirmatory methods were performed to identify the optimal scoring solution. Both the global score and the 2-subscale scoring solution showed adequate model fit. However, a χ2 difference test indicated that the 2-subscale scoring solution was a significantly better fit than the global score (P<0.05).ConclusionIf doctors or researchers would like to tease apart physical and psychosocial issues, the 2-subscale scoring solution would be recommended, since this solution showed to be optimal in scoring the CushingQoL. Regardless of the scoring solution used, the CushingQoL has proven to be a valuable resource for assessing health-related QoL in patients with CS.

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11

Clarke, Stephen R. "Dynamic Programming in One-Day Cricket-Optimal Scoring Rates." Journal of the Operational Research Society 39, no. 4 (1988): 331. http://dx.doi.org/10.2307/2582112.

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Le Thi, Hoai An, and Duy Nhat Phan. "DC programming and DCA for sparse optimal scoring problem." Neurocomputing 186 (April 2016): 170–81. http://dx.doi.org/10.1016/j.neucom.2015.12.068.

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13

Clarke, Stephen R. "Dynamic Programming in One-Day Cricket-Optimal Scoring Rates." Journal of the Operational Research Society 39, no. 4 (1988): 331–37. http://dx.doi.org/10.1057/jors.1988.60.

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Li, Guo-Quan, Xu-Xiang Duan, and Chang-Zhi Wu. "A New DC Algorithm for Sparse Optimal Scoring Problem." IEEE Access 8 (2020): 53962–71. http://dx.doi.org/10.1109/access.2020.2981429.

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15

Hu, C., X. Li, and J. Liang. "Developing optimal non-linear scoring function for protein design." Bioinformatics 20, no. 17 (2004): 3080–98. http://dx.doi.org/10.1093/bioinformatics/bth369.

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Clarke, Stephen R. "Dynamic Programming in One-Day Cricket—Optimal Scoring Rates." Journal of the Operational Research Society 39, no. 4 (1988): 331–37. http://dx.doi.org/10.1057/palgrave.jors.0390401.

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Li, Guoquan, Xuxiang Duan, Zhiyou Wu, and Changzhi Wu. "Generalized elastic net optimal scoring problem for feature selection." Neurocomputing 447 (August 2021): 183–95. http://dx.doi.org/10.1016/j.neucom.2021.03.018.

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18

Velykoivanenko, Halyna, Svitlana Savina, Dmitriy Kolechko, and Vladyslav Ben’. "Building the ensembles of credit scoring models." Neuro-Fuzzy Modeling Techniques in Economics 7, no. 1 (2019): 21–43. http://dx.doi.org/10.21511/nfmte.7.2018.02.

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The article is devoted to solving the actual problem of increasing the efficiency of assessing the credit risks of individual borrowers by finding the optimal combination of the results of calculations of specific scoring models. The principles of the formation of an ensemble of models are given and the existing approaches to the construction of ensemble structures are analyzed. In the process of experimental research has been applied one of the modifications of the boosting algorithm and implemented the author's algorithm for constructing an ensemble of models based on the specialization of experts. The radial-basis function neural networks were used as specific expert models. As a result of a comparative analysis of the efficiency of the used ensemble technologies it was confirmed that the algorithm for constructing an ensemble based on the specialization of experts proposed by the authors is the most adapted for the task of assessing credit risk.

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19

Chen, Heng, and Di-Rong Chen. "Statistical performance of optimal scoring in reproducing kernel Hilbert spaces." Journal of Statistical Planning and Inference 194 (March 2018): 122–35. http://dx.doi.org/10.1016/j.jspi.2017.09.001.

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20

Dionne, Georges, Florence Giuliano, and Pierre Picard. "Optimal Auditing with Scoring: Theory and Application to Insurance Fraud." Management Science 55, no. 1 (2009): 58–70. http://dx.doi.org/10.1287/mnsc.1080.0905.

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21

Ortner, Irene, Peter Filzmoser, and Christophe Croux. "Robust and sparse multigroup classification by the optimal scoring approach." Data Mining and Knowledge Discovery 34, no. 3 (2020): 723–41. http://dx.doi.org/10.1007/s10618-019-00666-8.

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22

Lederhandler, Margo, and Roy Geronemus. "Scoring of the Vermilion Lip for Optimal Post-Surgical Realignment." Journal of Drugs in Dermatology 20, no. 4 (2021): 486. http://dx.doi.org/10.36849/jdd.5411.

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23

Picco, Louisa, Melissa Middleton, Raimondo Bruno, Michala Kowalski, and Suzanne Nielsen. "Validation of the OWLS, a Screening Tool for Measuring Prescription Opioid Use Disorder in Primary Care." Pain Medicine 21, no. 11 (2020): 2757–64. http://dx.doi.org/10.1093/pm/pnaa275.

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Abstract Objective The OWLS is a screening tool for prescription opioid use disorder designed for use in primary care. This study aimed to confirm the optimal wording, scoring methods, and cutoff for the OWLS. Design and Setting Cross-sectional analysis of an online sample. Subjects Participants comprised those with chronic noncancer pain who regularly used prescription opioids. Methods Eligible participants self-completed an online version of the OWLS prescription opioid use disorder screening tool and the Composite International Diagnostic Interview Substance Abuse module. Receiver operating characteristics were calculated for three scoring methods for the OWLS, and these were compared with DSM-5 classification of any use disorder and moderate to severe opioid use disorder. Results Among the sample (N = 324), utilizing scoring method (i) (i.e., positive endorsement ≥ response option “a little bit”) and a cutoff of 3 increased the percentage of correctly classified participants, with concurrent increases in specificity and decreases in false discovery rate, and false positive rate. Conclusion OWLS utilizing scoring method (i) with a cutoff of 3 was shown to be the optimal version and scoring method of this tool. This represents a time-efficient, simple scoring method, allowing for quick and accurate screening for opioid use disorder to occur.

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24

Pavlova, E. V., and V. V. Roskoshenko. "Segmentation of retail bank customers for the purposes of modeling the loan claim default." Finance and Credit 26, no. 11 (2020): 2594–616. http://dx.doi.org/10.24891/fc.26.11.2594.

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Subject. In the banking practice, approaches to separate modeling of loan claim default (for new and repeat customers, for customers having and not having a history in the Credit Bureau, etc.) are widespread. Such a segmentation of retail bank customers may increase the efficiency of applied scoring system. The practical problem of choosing the optimal heuristic method of segmentation for the scoring remains unresolved. Objectives. The purpose of this work is to determine the optimal heuristic method of segmentation from those that are known in the literature and the industry. Methods. The study employs statistical analysis and content analysis of information sources. Results. We compared over thirty heuristic methods for segmentation of retail bank customers. The comparison showed that according to the classifier of the efficiency metric (AUROC), our proposed segmentation by the disbursed loan size turned out to be optimal. The method consists in the ‘disbursed loan’ variable discretization under the TreeR method. Conclusions and Relevance. The findings may be helpful in loan scoring and in any statistical modeling, using the logit regression.

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25

Gaynanova, Irina. "Prediction and estimation consistency of sparse multi-class penalized optimal scoring." Bernoulli 26, no. 1 (2020): 286–322. http://dx.doi.org/10.3150/19-bej1126.

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26

Ando, Tomohiro. "Penalized optimal scoring for the classification of multi-dimensional functional data." Statistical Methodology 6, no. 6 (2009): 565–76. http://dx.doi.org/10.1016/j.stamet.2009.06.003.

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27

Watson, Stennis G., Kenneth J. Sufka, and Terence J. Coderre. "Optimal scoring strategies and weights for the formalin test in rats." Pain 70, no. 1 (1997): 53–58. http://dx.doi.org/10.1016/s0304-3959(96)03299-x.

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28

Fellingham, Gilbert W., Bruce Jay Collings, and Carl M. McGown. "Developing an Optimal Scoring System with a Special Emphasis on Volleyball." Research Quarterly for Exercise and Sport 65, no. 3 (1994): 237–43. http://dx.doi.org/10.1080/02701367.1994.10607624.

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29

Huang, Sheau-Ling, Ching-Lin Hsieh, Jau-Hong Lin, and Hui-Mei Chen. "Optimal scoring methods of hand-strength tests in patients with stroke." International Journal of Rehabilitation Research 34, no. 2 (2011): 178–80. http://dx.doi.org/10.1097/mrr.0b013e328342dd96.

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30

Krakovská, Anna, and Kristína Mezeiová. "Automatic sleep scoring: A search for an optimal combination of measures." Artificial Intelligence in Medicine 53, no. 1 (2011): 25–33. http://dx.doi.org/10.1016/j.artmed.2011.06.004.

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Ghanima, Waleed, Per Sandset, Susan Kahn, and Hilde Wik. "Scoring Systems for Postthrombotic Syndrome." Seminars in Thrombosis and Hemostasis 43, no. 05 (2017): 500–504. http://dx.doi.org/10.1055/s-0037-1599142.

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AbstractPostthrombotic syndrome (PTS) is the most common long-term complication after deep vein thrombosis (DVT) and is associated with reduced quality of life. There is no single objective test to diagnose the presence of PTS and it is usually diagnosed on the basis of typical symptoms and signs in a limb previously affected by DVT. Scoring systems for PTS are primarily developed as research tools, but could possibly also be useful in the clinical setting. A main advantage of a good scoring system is standardization of the diagnostic process. An optimal scoring system should be both sensitive and specific for PTS, but this has been difficult to achieve because the symptoms and signs of PTS can be similar to other conditions leading to complaints in the lower limb. In an effort to standardize the definition of PTS, in 2009, the International Society on Thrombosis and Haemostasis Subcommittee on Control of Anticoagulation reviewed available scales and recommended use of the Villalta scale as the most appropriate measure to diagnose and grade the severity of PTS. The aim of this article is to review the existing scoring systems for PTS and to present our view on the advantages and disadvantages of these diagnostic tools.

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Guo, Qiucen, Hui Yang, and Huan He. "Based on the study of optimal pollutant control in yingkou section of daliaohe river." E3S Web of Conferences 228 (2021): 02015. http://dx.doi.org/10.1051/e3sconf/202122802015.

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In view of the complexity of the river flowing into yingkou section of daliaohe river, an optimal pollutant control screening method combining the migration and degradation of toxic and harmful pollutants was proposed to improve the comprehensive scoring method. The weight factors of 10 synthetic scoring methods were proposed, and different weights were assigned to the weight factors, focusing more on the migration and degradation of pollutants. The improved comprehensive score method was used to screen 39 pollutants in the list of potential pollutants. Twelve kinds.

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Yamakawa, Kazuma, Yutaka Umemura, Shuhei Murao, Mineji Hayakawa, and Satoshi Fujimi. "Optimal Timing and Early Intervention With Anticoagulant Therapy for Sepsis-Induced Disseminated Intravascular Coagulation." Clinical and Applied Thrombosis/Hemostasis 25 (January 1, 2019): 107602961983505. http://dx.doi.org/10.1177/1076029619835055.

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Optimizing diagnostic criteria to detect specific patients likely to benefit from anticoagulants is warranted. A cutoff of 5 points for the International Society on Thrombosis and Haemostasis overt disseminated intravascular coagulation (DIC) scoring system was determined in the original article, but its validity was not evaluated. This study aimed to explore the optimal cutoff points of DIC scoring systems and evaluate the effectiveness of early intervention with anticoagulants. We used a nationwide retrospective registry of consecutive adult patients with sepsis in Japan to develop simulated survival data, assuming anticoagulants were conducted strictly according to each cutoff point. Estimated treatment effects of anticoagulants for in-hospital mortality and risk of bleeding were calculated by logistic regression analysis with inverse probability of treatment weighting using propensity scoring. Of 2663 patients with sepsis, 1247 patients received anticoagulants and 1416 none. The simulation model showed no increase in estimated mortality between 0 and 3 cutoff points, whereas at ≥4 cutoff points, mortality increased linearly. The estimated bleeding tended to decrease in accordance with the increase in cutoff points. The optimal cutoff for determining anticoagulant therapy may be 3 points to minimize nonsurvival with acceptable bleeding complications. The findings of the present study suggested a beneficial association of early intervention with anticoagulant therapy and mortality in the patients with sepsis-induced DIC. Present cutoff points of DIC scoring systems may be suboptimal for determining the start of anticoagulant therapy and delay its initiation.

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Juvela, Seppo. "Scoring of Growth of Unruptured Intracranial Aneurysms." Journal of Clinical Medicine 9, no. 10 (2020): 3339. http://dx.doi.org/10.3390/jcm9103339.

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The purpose was to obtain a reliable scoring for growth of unruptured intracranial aneurysms (UIAs) in a long-term follow-up study from variables known at baseline and to compare it with the ELAPSS (Earlier subarachnoid hemorrhage, Location of the aneurysm, Age > 60 years, Population, Size of the aneurysm, and Shape of the aneurysm) score obtained from an individual-based meta-analysis. The series consists of 87 patients with 111 UIAs and 1669 person-years of follow-up between aneurysm size measurements (median follow-up time per patient 21.7, range 1.2 to 51.0 years). These were initially diagnosed between 1956 and 1978, when UIAs were not treated in our country. ELAPSS scores at baseline did not differ between those with and those without aneurysm growth. The area under the curve (AUC) for the receiver operating curve (ROC) of the ELAPSS score for predicting long-term growth was fail (0.474, 95% CI 0.345–0.603), and the optimal cut-off point was obtained at ≥7 vs. <7 points for sensitivity (0.829) and specificity (0.217). In the present series UIA growth was best predicted by female sex (4 points), smoking at baseline (3 points), and age <40 years (2 points). The AUC for the ROC of the new scoring was fair (0.662, 95% CI 0.546–0.779), which was significantly better than that of ELAPSS score (p < 0.05). The optimal cut-off point was obtained at ≥4 vs. <4 points for sensitivity (0.971) and specificity (0.304). A new simple scoring consisting of only female sex, cigarette smoking and age <40 years predicted growth of an intracranial aneurysm in long-term follow-up, significantly better than the ELAPSS score.

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35

SATO, NOBUYOSHI, MINORU UEHARA, and YOSHIFUMI SAKAI. "EVALUATIONS OF FRESHNESS CONSIDERING SCORING ON FRESH INFORMATION RETRIEVAL." Journal of Interconnection Networks 06, no. 03 (2005): 265–82. http://dx.doi.org/10.1142/s0219265905001423.

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Fresh information is important for real business. In order to realize fresh information retrieval, we need not only to collect documents in a short time, but also to rank the results in the suitable order. However, conventional ranking methods are not suited for fresh information retrieval because they ignore temporal value of information. So, we have proposed the novel ranking method FTF·IDF for fresh information retrieval. FTF·IDF extends TF·IDF by means of using FTF (Fresh Term Frequency) instead of TF (Term Frequency). FTF differs from TF because FTF decreases as time goes. The speed of decreasing FTF is determined by the dumping factor. The dumping factor is sensitive against small changes of documents. So, we use a threshold to ignore such small changes. In some papers we published, we detect the optimal threshold manually. In this paper, we proposed an adaptive calculating method in order to detect threshold automatically. In this method, the optimal value is determined by iterating to test generated thresholds. In this paper, we describe our method and its evaluation.

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Phan, Duy Nhat, та Hoai An Le Thi. "Group variable selection via ℓp,0 regularization and application to optimal scoring". Neural Networks 118 (жовтень 2019): 220–34. http://dx.doi.org/10.1016/j.neunet.2019.05.011.

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Li, Yang, Marie‐Anne S. Rosemberg, Vanessa K. Dalton, Shawna J. Lee, and Julia S. Seng. "Exploring the optimal allostatic load scoring method in women of reproductive age." Journal of Advanced Nursing 75, no. 11 (2019): 2548–58. http://dx.doi.org/10.1111/jan.14014.

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Dobson, Rebecca, Daniel J. Cuthbertson, Julia Jones, et al. "Determination of the Optimal Echocardiographic Scoring System to Quantify Carcinoid Heart Disease." Neuroendocrinology 99, no. 2 (2014): 85–93. http://dx.doi.org/10.1159/000360767.

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Chambers, Christopher P., Paul J. Healy, and Nicolas S. Lambert. "Proper scoring rules with general preferences: A dual characterization of optimal reports." Games and Economic Behavior 117 (September 2019): 322–41. http://dx.doi.org/10.1016/j.geb.2019.07.012.

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40

Hopwood, Christopher J., Suzannah K. Creech, Timothy S. Clark, Mary W. Meagher, and Leslie C. Morey. "Optimal Scoring of the Multidimensional Pain Inventory in a Chronic Pain Sample." Journal of Clinical Psychology in Medical Settings 15, no. 4 (2008): 301–7. http://dx.doi.org/10.1007/s10880-008-9131-x.

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Ford, Linda K., Joshua D. Borneman, Julia Krebs, Evguenia A. Malaia, and Brendan P. Ames. "Classification of visual comprehension based on EEG data using sparse optimal scoring." Journal of Neural Engineering 18, no. 2 (2021): 026025. http://dx.doi.org/10.1088/1741-2552/abdb3b.

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Ankirchner, Stefan, Christophette Blanchet-Scalliet, and Kai Kümmel. "Last minute panic in zero sum games." ESAIM: Control, Optimisation and Calculus of Variations 25 (2019): 25. http://dx.doi.org/10.1051/cocv/2018015.

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We set up a game theoretical model to analyze the optimal attacking intensity of sports teams during a game. We suppose that two teams can dynamically choose among more or less offensive actions and that the scoring probability of each team depends on both teams’ actions. We assume a zero sum setting and characterize a Nash equilibrium in terms of the unique solution of an Isaacs equation. We present results from numerical experiments showing that a change in the score has a strong impact on strategies, but not necessarily on scoring intensities. We give examples where strategies strongly depend on the score, the scoring intensities not at all.

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Xiang, Ling, Andrea Hsiu Ling Low, Ying Ying Leung, et al. "Improving sensitivity of the connective tissue disease screening questionnaire: A comparative study of various scoring methods." Lupus 30, no. 1 (2020): 35–44. http://dx.doi.org/10.1177/0961203320966378.

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Objectives Early detection of autoimmune rheumatic diseases is crucial given their high morbidity and mortality and short window of opportunity to improve patient outcomes. Self-administered screening questionnaires such as the connective tissue disease screening questionnaire (CSQ) have been shown to promote early detection of autoimmune rheumatic diseases. However, optimal scoring of screening questionnaires may differ with prevalence of clinical features and changes in classification criteria. We compared the performance of 3 scoring methods for the CSQ for early detection of autoimmune rheumatic diseases in a multi-ethnic Asian population. Methods Patients who were newly referred for evaluation of possible autoimmune rheumatic diseases were invited to answer the cross-culturally adapted CSQ. Detection of autoimmune rheumatic diseases using 1) the original CSQ scoring, 2) a modified CSQ scoring and 3) a scoring based on current classification criteria, were compared to classification of autoimmune rheumatic diseases by classification criteria. Results Of 819 participants, 85 were classified as having autoimmune rheumatic diseases screened for by the adapted CSQ. The original CSQ scoring yielded relatively lower sensitivities in detecting both any and individual autoimmune rheumatic diseases (67% and 20-57%, respectively) compared to the modified CSQ scoring (81% and 60-73%, respectively) and the scoring based on current classification criteria (89% and 50-88%, respectively). Conclusion The adapted CSQ with the classification criteria-based scoring achieved relatively high sensitivities in detecting autoimmune rheumatic diseases, suggesting this could be employed as the first step in population screening.

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Ye, Lei, Can Wang, Xin Xu та Wei Chen. "Multi-class ℓ2-Boost with the scoring coding". International Journal of Wavelets, Multiresolution and Information Processing 14, № 06 (2016): 1650049. http://dx.doi.org/10.1142/s0219691316500491.

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Boosting, one of the best off-the-shelf classification methods, has evoked widespread interest in machine learning and statistics. However, the original algorithm was developed for binary classification problems. In this paper, we study multi-class boosting algorithms under the [Formula: see text]-loss framework, and devise two multi-class [Formula: see text]-Boost algorithms. These are based on coordinate descent and gradient descent to minimize the multi-class [Formula: see text]-loss function. We derive a scoring coding scheme using optimal scoring constraints to encode class labels and a simple decoder to recover the true class labels. Our boosting algorithms are easily implemented and their results converge to the global optimum. Experiments with synthetic and real-world datasets show that, compared with several state-of-art methods, our algorithms provide more accurate results.

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45

Mochizuki, Tomoharu, Osamu Tanifuji, Takashi Sato, Satoshi Watanabe, Go Omori, and Naoto Endo. "Scoring system for optimal management of acute traumatic patellar dislocation: A multicenter study." Journal of Orthopaedic Science 25, no. 1 (2020): 173–77. http://dx.doi.org/10.1016/j.jos.2019.03.009.

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46

Gregory, Jesse. "Do basketball scoring patterns reflect illegal point shaving or optimal in-game adjustments?" Quantitative Economics 9, no. 2 (2018): 1053–85. http://dx.doi.org/10.3982/qe519.

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47

Leng, Chenlei. "Sparse optimal scoring for multiclass cancer diagnosis and biomarker detection using microarray data." Computational Biology and Chemistry 32, no. 6 (2008): 417–25. http://dx.doi.org/10.1016/j.compbiolchem.2008.07.015.

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Willemink, Martin J., Annemarie M. den Harder, Wouter Foppen, et al. "Finding the optimal dose reduction and iterative reconstruction level for coronary calcium scoring." Journal of Cardiovascular Computed Tomography 10, no. 1 (2016): 69–75. http://dx.doi.org/10.1016/j.jcct.2015.08.004.

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Handoko, Bagus Dwi, Ari Suwondo, and Jeffri Ardiyanto. "Optimalisasi Citra dalam Penghitungan Calsium Scoring dengan Variasi Scan Type dan Slice Thickness (Studi Pendahuluan Dilakukan Dengan Menggunakan Modifikasi Phantom Thorax di RS Telogorejo Semarang)." Jurnal Imejing Diagnostik (JImeD) 1, no. 1 (2015): 10–13. http://dx.doi.org/10.31983/jimed.v1i1.3152.

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Background : Examination of Calcium scoring in Radiology Departement Telogorejo Hospital Semarang using CINE scan type and recon phase images using a slice thickness of 2.5mm, this affect will be plaque with small size cann’t to calculate. Aim : The Purpose of this study was to determine the variation of parameters of calcium scoring MSCT scan examination right in calculating optimal plaque.Methods : The study was preceded by Pre experiments using a thorax phantom with an added 3-calcium artificial heart is likened to the RCA, LCX, LAD and have determined the weight and volume. Experiments with 10 patient samples by applying the best parameters from the pre experiment. Statistical analysis of the results of research conducted by Paired T-Test, while the assessment of the quality radiographs evaluated by an expert in this specialist radiology by providing anatomical criteria scores with 3 choices of items (not clear = 1, is quite clear = 2 and obvious = 3)Result : The volume of plaque is embedded in the thorax Panthom 900mm3. Results of pre experiments with hellical scan type and pitch of 0.5, 0.9, 1.3 in a score of plaque volume is 104mm3, 67mm3, 60mm3. While the scan type CINE with slice thickness 0.625mm, 1.25mm, 2.5mm produces a score of volume plaque is 880mm3, 878mm3, 867mm3. Further experiments were performed by applying parameters with the best result is CINE scan with variations slice thickness 0,625mm, 1.25mm, 2.5mm. To determine the best parameters assessment of image quality with the results on slice thickness 0.625mm was 2.2 (quite obvious), slice thickness 1,25mm scoring average of 2.7 (quite obvious), and slice thickness 2.5 mm average scoring 2.9 (obviously). While image noise on the slice thickness 0.625mm, 1.25mm, 2.5mm, namely 2.7(very high), 1.6 (low), 1.1 (low).Conclusions : Selected parameters that calculate optimal scoring calcium and low noise image for MSCT scan calcium scoring in Telogorejo Hospital Semarang is Scan type CINE with slice thickness variation 1,25mm

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Ganicheva, A. V., and A. V. Ganichev. "VECTOR MODEL FOR MULTI-CRITERIA SCORING." Scientific Review: Theory and Practice 10, no. 10 (2020): 2245–53. http://dx.doi.org/10.35679/2226-0226-2020-10-10-2245-2253.

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To assess the performance of economic systems, criteria and performance indicators are used that show the degree of achievement of the desired performance result. To characterize complex systems in most real cases, one criterion is not enough. Therefore, several criteria are used to comprehensively characterize the system. The multi-criteria problem raises the problem of matching individual criteria when used together. There are many ways to select alternatives in the face of multiple decision criteria. This article discusses the multi-criteria comparison of objects with Pareto dominance, vector estimates with arbitrary non-negative coordinates of vectors. The advantages of vector estimates in comparison with average estimates are considered. In this work, three important theorems of multi-criteria estimation are proved. The theorems define the conditions for the equivalence of three options for comparing objects by a variety of attributes: 1) arithmetic mean values; 2) the lengths of the corresponding vectors; 3) scalar products of vectors. As the research results, the application of the developed methods for aggregating the quality indicators of the educational process into a single assessment is shown. The following indicators of the educational process were used: coefficient of diligence, coefficient of interest, coefficient of difficulty of mastering the studied material, assessment of academic performance. A four-criteria optimization problem is formulated. It is shown that the objective function reaches its extreme value at the point that is as close as possible to the point of the optimal solution of the formulated problem. The issues of multi-criteria assessment developed in the article can find application in the management of the educational process in the formation of individual trajectories of trainees, in the tasks of working with the personnel of firms and organizations (selection, training, retraining), in assessing the quality of products and in other areas of activity.

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