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
doaj +5 more sources
The genetic interpretation of area under the ROC curve in genomic profiling. [PDF]
PLoS Genetics, 2010 Genome-wide association studies in human populations have facilitated the creation of genomic profiles which combine the effects of many associated genetic variants to predict risk of disease.
Naomi R Wray +3 more
doaj +8 more sources
An analytic expression for the binormal partial area under the ROC curve. [PDF]
Acad Radiol, 2012 The partial area under the receiver operating characteristic (ROC) curve (pAUC) is a useful summary measure for diagnostic studies. Unlike most summary measures that are functions of the ROC curve, researchers have not been aware of an analytic expression available for computing the pAUC for an ROC curve based on a latent binormal model.
Hillis SL, Metz CE.
europepmc +5 more sources
A boosting method for maximizing the partial area under the ROC curve [PDF]
BMC Bioinformatics, 2010 Background The receiver operating characteristic (ROC) curve is a fundamental tool to assess the discriminant performance for not only a single marker but also a score function combining multiple markers.
Eguchi Shinto, Komori Osamu
doaj +5 more sources
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
doaj +3 more sources
Nonparametric bootstrap methods for interval estimation of the area under the ROC curve with correlated diagnostic test data: application to whole-virus ELISA testing in swine [PDF]
Frontiers in Veterinary Science, 2023 Developing and evaluating novel diagnostic assays are crucial components of contemporary diagnostic research. The receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) are frequently used to evaluate diagnostic assays ...
Jinji Pang +8 more
doaj +2 more sources
Estimation of Area Under the ROC Curve under nonignorable verification bias. [PDF]
Stat Sin, 2018 The Area Under the Receiving Operating Characteristic Curve (AUC) is frequently used for assessing the overall accuracy of a diagnostic marker. However, estimation of AUC relies on knowledge of the true outcomes of subjects: diseased or non-diseased.
Yu W, Kim JK, Park T.
europepmc +6 more sources
The area under the ROC curve as a measure of clustering quality
Data Mining and Knowledge Discovery, 2022 The Area Under the the Receiver Operating Characteristics (ROC) Curve, referred to as AUC, is a well-known performance measure in the supervised learning domain. Due to its compelling features, it has been employed in a number of studies to evaluate and compare the performance of different classifiers.
Pablo Andretta Jaskowiak +2 more
exaly +3 more sources
Constructing Hypothetical Risk Data from the Area under the ROC Curve: Modelling Distributions of Polygenic Risk. [PDF]
PLoS ONE, 2016 BACKGROUND:Modeling studies using hypothetical polygenic risk data can be an efficient tool for investigating the effectiveness of downstream applications such as targeting interventions to risk groups to justify whether empirical investigation is ...
Suman Kundu +2 more
doaj +2 more sources
On the Use of Min-Max Combination of Biomarkers to Maximize the Partial Area under the ROC Curve [PDF]
Journal of Probability and Statistics, 2019 Background. Evaluation of diagnostic assays and predictive performance of biomarkers based on the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) are vital in diagnostic and targeted medicine.
Hua Ma, Susan Halabi, Aiyi Liu
doaj +2 more sources