Cited by 4,506Statistical Methods in EpidemiologyImbalanced Data Classification TechniquesArtificial Intelligence in Healthcare

Receiver Operating Characteristic Curve in Diagnostic Test Assessment

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Mandrekar, Jayawant N.·2010·Journal of Thoracic Oncology

Abstract

The performance of a diagnostic test in the case of a binary predictor can be evaluated using the measures of sensitivity and specificity. However, in many instances, we encounter predictors that are measured on a continuous or ordinal scale. In such cases, it is desirable to assess performance of a diagnostic test over the range of possible cutpoints for the predictor variable. This is achieved by a receiver operating characteristic (ROC) curve that includes all the possible decision thresholds from a diagnostic test result. In this brief report, we discuss the salient features of the ROC curve, as well as discuss and interpret the area under the ROC curve, and its utility in comparing two different tests or predictor variables of interest.

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Crossref · 10.1097/jto.0b013e3181ec173d

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Authors
Mandrekar, J. N.
Affiliations
Mayo Clinic (US)
Corresponding author
Mandrekar, Jayawant N.
Venue
Journal of Thoracic Oncology
Publisher
Elsevier BV
Published
2010-09
Volume
5
Issue
9
Pages
1315-1316
ISSN
1556-0864 (ISSN-L)
OpenAlex
W1980276147
Cited by
4,506
References
2
Citations by year
2026: 476 · 2025: 704 · 2024: 830 · 2023: 765 · 2022: 759 · 2021: 573 · 2020: 236 · 2019: 94 · 2018: 37 · 2017: 6 · 2016: 3 · 2015: 3 · 2014: 4 · 2013: 4 · 2012: 5
FWCI
3.82
Type
journal article
Language
en
Open access
Locations
  • Journal of Thoracic Oncology (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
  • Physical Sciences › Computer Science › Artificial Intelligence › Imbalanced Data Classification Techniques
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
Keywords
receiver operating characteristic, diagnostic performance, continuous predictors, decision threshold, area under the ROC curve, sensitivity and specificity, test comparison
MeSH terms
Diagnostic Tests, Routine, Humans, Neoplasms, Prognosis, ROC Curve, Sensitivity and Specificity

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