Unsupervised Learning for Automated Detection of Coronary Artery Disease Subgroups

Unsupervised Learning for Automated Detection of Coronary Artery Disease Subgroups

Background The promise of precision population health includes the ability to use robust patient data to tailor prevention and care to specific groups. Advanced analytics may allow for automated detection of clinically informative subgroups that account for clinical, genetic, and environmental varia...

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Bibliographic Details
Main Authors: Alyssa M. Flores, Alejandro Schuler, Anne Verena Eberhard, Jeffrey W. Olin, John P. Cooke, Nicholas J. Leeper, Nigam H. Shah, Elsie G. Ross
Format: Article
Language:English
Published: Wiley 2021-12-01
Series:Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
Subjects:
cluster analysis
coronary artery disease
machine learning
phenotype discovery
Online Access:https://www.ahajournals.org/doi/10.1161/JAHA.121.021976

Internet

https://www.ahajournals.org/doi/10.1161/JAHA.121.021976

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