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Article

Temporal phenome analysis of a large electronic health record cohort enables identification of hospital-acquired complications.

Journal of the American Medical Informatics Association : JAMIA - 1 Dec 2013

Warner Jeremy L, Zollanvari Amin, Ding Quan, Zhang Peijin, Snyder Graham M, Alterovitz Gil

Abstract excerpt

OBJECTIVE: To develop methods for visual analysis of temporal phenotype data available through electronic health records (EHR). MATERIALS AND METHODS: 24 580 adults from the multiparameter intelligent monitoring in intensive care V.6 (MIMIC II) EHR database of critically ill patients were analyzed, with significant temporal associations visualized as a map of associations between hospital length of stay (LOS) and...

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Identifiers

PMID: 23907284
DOI: 10.1136/amiajnl-2013-001861
PMCID: PMC3861919

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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