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Article

Detecting time-evolving phenotypic topics via tensor factorization on electronic health records: Cardiovascular disease case study.

Journal of biomedical informatics - 1 Oct 2019

Zhao Juan, Zhang Yun, Schlueter David J, Wu Patrick, Eric Kerchberger Vern, Trent Rosenbloom S, Wells Quinn S, Feng QiPing, Denny Joshua C, Wei Wei-Qi

Abstract excerpt

OBJECTIVE: Discovering subphenotypes of complex diseases can help characterize disease cohorts for investigative studies aimed at developing better diagnoses and treatments. Recent advances in unsupervised machine learning on electronic health record (EHR) data have enabled researchers to discover phenotypes without input from domain experts. However, most existing studies have ignored time and modeled diseases...

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Identifiers

PMID: 31445983
DOI: 10.1016/j.jbi.2019.103270
PMCID: PMC6783385

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