Results 31 to 40 of about 265,917 (163)
Minimum‐Norm Estimation for Binormal Receiver Operating Characteristic (ROC) Curves [PDF]
AbstractThe receiver operating characteristic (ROC) curve is often used to assess the usefulness of a diagnostic test. We present a new method to estimate the parameters of a popular semi‐parametric ROC model, called the binormal model. Our method is based on minimization of the functional distance between two estimators of an unknown transformation ...
Ori, Davidov, Yuval, Nov
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Background: Psychiatrists use different scales to evaluate post-stroke depression; however, some concerns have raised about their low specificity. Objectives: This study aimed to assess the validity and reliability of the Persian version of the Post ...
Somayeh Shokrgozar +5 more
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Acceptance sampling for attributes via hypothesis testing and the hypergeometric distribution
This paper questions some aspects of attribute acceptance sampling in light of the original concepts of hypothesis testing from Neyman and Pearson (NP).
Robert Wayne Samohyl
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ROCS: receiver operating characteristic surface for class-skewed high-throughput data. [PDF]
The receiver operating characteristic (ROC) curve is an important tool to gauge the performance of classifiers. In certain situations of high-throughput data analysis, the data is heavily class-skewed, i.e.
Tianwei Yu
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Receiver Operating Characteristic (ROC) Curves
Receiver operating characteristic (ROC) curves are used ubiquitously to evaluate covariates, markers, or features as potential predictors in binary problems. We distinguish raw ROC diagnostics and ROC curves, elucidate the special role of concavity in interpreting and modelling ROC curves, and establish an equivalence between ROC curves and cumulative ...
Gneiting, Tilmann, Vogel, Peter
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A Linear Regression Framework for the Receiver Operating Characteristic(ROC) Curve Analysis [PDF]
The receiver operating characteristic (ROC) curve has been a popular statistical tool for characterizing the discriminating power of a classifier, such as a biomarker or an imaging modality for disease screening or diagnosis. It has been recognized that the accuracy of a given procedure may depend on some underlying factors, such as subject's ...
Zhang, Zheng, Huang, Ying
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Combining biomarkers and their statistics is used to increase the prediction performance of a diagnosis, but no gold standard method exists. We introduced and evaluated an approach using linear combinations of summary-based statistics tested in logistic ...
Ilie-Andrei CONDURACHE +1 more
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Predicting Customer’s Satisfaction (Dissatisfaction) Using Logistic Regression [PDF]
Customer satisfaction is a metric of how products and services offered by companies meet customer expectations. This performance indicator assists companies in managing and monitoring their business effectively.
Adarsh Anand, Gunjan Bansal
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Identifying Potential miRNAs–Disease Associations With Probability Matrix Factorization
In recent years, miRNAs have been verified to play an irreplaceable role in biological processes associated with human disease. Discovering potential disease-related miRNAs helps explain the underlying pathogenesis of the disease at the molecular level ...
Junlin Xu +8 more
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Background: The viral neutralization assay is the gold standard to estimate the level of immunity against SARS-CoV-2. This study analyzes the correlation between the quantitative Anti-SARS-CoV-2 QuantiVac ELISA (IgG) and the NeutraLISA neutralization ...
Engy Mohamed El-Ghitany +3 more
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