ArticleStatistical methods in medical research2021
Revisiting performance metrics for prediction with rare outcomes.
Article in Statistical methods in medical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Development and internal-external validation of statistical and machine learning models for breast cancer prognostication: cohort study.BMJ (Clinical research ed.) · 2023Pooled it
- Development of a Screening Model for Exercise-Induced Desaturation by Machine Learning Method.Tuberculosis and respiratory diseases · 2026Article
- Beyond Area Under the Receiver Operating Characteristic Curve: Evaluating Predictive Performance Metrics Under Class Imbalance in Real-World Clinical Data.JMIR formative research · 2026Article
- Evaluation of trajectory analysis for disease risk assessment: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Behavior of prediction performance metrics with rare events.Journal of clinical epidemiology · 2026Article
- Detecting Perceived Unfair Treatment Among US College Students Using Mobile Sensing: Pilot Machine Learning Study.JMIR formative research · 2025Article
- Advancing thyroid diagnosis: integrating AI-driven CAD framework with numerical data and ultrasound images.PeerJ. Computer science · 2025Article
- Examining the relationship between emotion regulation, sleep quality, and anxiety disorder diagnosis.Journal of mood and anxiety disorders · 2024Article
- Predicting adolescent psychopathology from early life factors: A machine learning tutorial.Global epidemiology · 2024Article
- Testing and characterization of herding dogs' behaviors.Journal of animal science · 2024Article
- Innovative models for enhanced student adaptability and performance in educational environments.PloS one · 2024Article
- Automated analysis of low-field brain MRI in cerebral malaria.Biometrics · 2023Article
- Promising Administrative Measures of Heart Failure and Future Directions.Circulation. Cardiovascular quality and outcomes · 2023Article
- Article
- Artificial Intelligence in Breast Cancer Screening: Evaluation of FDA Device Regulation and Future Recommendations.JAMA internal medicine · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 4 institutions in 1 country.
Funding
Abstract
Machine learning algorithms are increasingly used in the clinical literature, claiming advantages over logistic regression. However, they are generally designed to maximize the area under the receiver operating characteristic curve. While area under the receiver operating characteristic curve and other measures of accuracy are commonly reported for evaluating binary prediction problems, these metrics can be misleading. We aim to give clinical and machine learning researchers a realistic medical example of the dangers of relying on a single measure of discriminatory performance to evaluate binary prediction questions. Prediction of medical complications after surgery is a frequent but challenging task because many post-surgery outcomes are rare. We predicted post-surgery mortality among patients in a clinical registry who received at least one aortic valve replacement. Estimation incorporated multiple evaluation metrics and algorithms typically regarded as performing well with rare outcomes, as well as an ensemble and a new extension of the lasso for multiple unordered treatments. Results demonstrated high accuracy for all algorithms with moderate measures of cross-validated area under the receiver operating characteristic curve. False positive rates were
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.