Results 1 to 10 of about 2,344,066 (336)
Area under the ROC Curve has the most consistent evaluation for binary classification [PDF]
PLoS ONEThe proper use of model evaluation metrics is important for model evaluation and model selection in binary classification tasks. This study investigates how consistent different metrics are at evaluating models across data of different prevalence while ...
Jing Li
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A relationship between the incremental values of area under the ROC curve and of area under the precision-recall curve [PDF]
Diagnostic and Prognostic Research, 2021 Background Incremental value (IncV) evaluates the performance change between an existing risk model and a new model. Different IncV metrics do not always agree with each other. For example, compared with a prescribed-dose model, an ovarian-dose model for
Qian M. Zhou +4 more
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Induction Motor Fault Classification Based on ROC Curve and t-SNE
IEEE Access, 2021 This paper proposes a novel fault classification method with application to induction motors, which is based on integrating and combining with receiver operating characteristic (ROC) curve and t-distribution stochastic neighbor embedding (t-SNE ...
Chun-Yao Lee, Wen-Cheng Lin
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Smooth ROC curve estimation via Bernstein polynomials. [PDF]
PLoS ONE, 2021 The receiver operating characteristic (ROC) curve is commonly used to evaluate the accuracy of a diagnostic test for classifying observations into two groups.
Dongliang Wang, Xueya Cai
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Model-Based ROC Curve: Examining the Effect of Case Mix and Model Calibration on the ROC Plot. [PDF]
Med Decis Making, 2022 Background The performance of risk prediction models is often characterized in terms of discrimination and calibration. The receiver-operating characteristic (ROC) curve is widely used for evaluating model discrimination.
Sadatsafavi M +2 more
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Web-Bootstrap Estimate of Area Under ROC Curve
Austrian Journal of Statistics, 2016 The accuracy of binary discrimination models (discrimination between cases with and without any condition) is usually summarized by classification matrix (also called a confusion, assignment, or prediction matrix). Receiver operating characteristic (ROC)
Hana Skalská, Václav Freylich
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ROC curve analysis: a useful statistic multi-tool in the research of nephrology. [PDF]
Int Urol NephrolIn the past decade, scientific research in the area of Nephrology has focused on evaluating the clinical utility and performance of various biomarkers for diagnosis, risk stratification and prognosis.
Roumeliotis S +8 more
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Time-dependent ROC curve analysis in medical research: current methods and applications
BMC Medical Research Methodology, 2017 Background ROC (receiver operating characteristic) curve analysis is well established for assessing how well a marker is capable of discriminating between individuals who experience disease onset and individuals who do not.
Adina Najwa Kamarudin +2 more
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Revstat Statistical Journal, 2014 This work overviews some developments on the estimation of the Receiver Operating Characteristic (ROC) curve. Estimation methods in this area are constantly being developed, adjusted and extended, and it is thus impossible to cover all topics and areas ...
Luzia Gonçalves +3 more
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The receiver operating characteristic (ROC) curve
Southwest Respiratory and Critical Care Chronicles, 2017 Corresponding author: Shengping Yang Contact Information: Shengping.yang@ttuhsc.edu DOI: 10.12746/swrccc.v5i19.391 Results from routine blood tests can be used potentially as biomarkers for identifying disease.
Shengping Yang, Gilbert Berdine
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