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Article

Predicting age by mining electronic medical records with deep learning characterizes differences between chronological and physiological age.

Journal of biomedical informatics - 1 Dec 2017

Wang Zichen, Li Li, Glicksberg Benjamin S, Israel Ariel, Dudley Joel T, Ma'ayan Avi

Abstract excerpt

Determining the discrepancy between chronological and physiological age of patients is central to preventative and personalized care. Electronic medical records (EMR) provide rich information about the patient physiological state, but it is unclear whether such information can be predictive of chronological age. Here we present a deep learning model that uses vital signs and lab tests contained within the EMR of...

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Identifiers

PMID: 29113935
DOI: 10.1016/j.jbi.2017.11.003
PMCID: PMC5716867

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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