Detecting Time-Evolving Phenotypic Topics via Tensor Factorization on Electronic Health Records: Cardiovascular Disease Case Study

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 p...

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Detalhes bibliográficos
Publicado no:J Biomed Inform
Main Authors: Zhao, Juan, Zhang, Yun, Schlueter, David J., Wu, Patrick, Kerchberger, Vern Eric, Rosenbloom, S. Trent, Wells, Quinn S., Feng, QiPing, Denny, Joshua C., Wei, Wei-Qi
Formato: Artigo
Idioma:Inglês
Publicado em: 2019
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6783385/
https://ncbi.nlm.nih.gov/pubmed/31445983
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jbi.2019.103270
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