Performance metric curve analysis framework to assess impact of the decision variable threshold, disease prevalence, and dataset variability in two-class classification-Reference-Cited by-同舟云学术

Performance metric curve analysis framework to assess impact of the decision variable threshold, disease prevalence, and dataset variability in two-class classification

Published:2022-05-31 Issue:03 Volume:9 Page:
ISSN:2329-4302
Container-title:Journal of Medical Imaging
language:
Short-container-title:J. Med. Imag.

Author:

Whitney Heather M.¹,Drukker Karen¹,Giger Maryellen L.¹

Affiliation:

1. University of Chicago, Department of Radiology, Chicago, Illinois

Funder

National Institutes of Health

NIH

HHS|NIH|National Cancer Institute

Publisher

SPIE-Intl Soc Optical Eng

Subject

Radiology, Nuclear Medicine and imaging

Reference47 articles.

1. Basic principles of ROC analysis

2. Caveats and pitfalls of ROC analysis in clinical microarray research (and how to avoid them)

3. The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets

4. On the Binormal Predictive Receiver Operating Characteristic Curve for the Joint Assessment of Positive and Negative Predictive Values

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