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This paper is in the following e-collection/theme issue:

Data Science (729) Clinical Information and Decision Making (3910) New Methods (1874) Tools, Programs and Algorithms (610) Decision Support for Health Professionals (2361) Machine Learning (3353) Aging with Chronic Disease (553) Artificial Intelligence (5056)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71592, first published .
Diverse group of people with health monitoring gauges indicating well-being

Biological Age Estimation From the Age Gap Using Deep Learning Integrating Morbidity and Mortality: Model Development and Validation Study

Biological Age Estimation From the Age Gap Using Deep Learning Integrating Morbidity and Mortality: Model Development and Validation Study

Authors of this article:

Seong-Eun Moon1 Author Orcid Image ;   Ji Won Yoon2, 3 Author Orcid Image ;   Jae Hyun Bae3, 4 Author Orcid Image ;   Shinyoung Joo1 Author Orcid Image ;   Yoo Hyung Kim4 Author Orcid Image ;   Bon Hyang Lee4 Author Orcid Image ;   Seokho Yoon5 Author Orcid Image ;   Haanju Yoo1 Author Orcid Image ;   Young Min Cho3, 4 Author Orcid Image
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Journals

  1. Saliev T, Singh P. From Chronology to Physiology: A Critical Translational Assessment of Artificial Intelligence for Precision Healthspan Measurement. International Journal of Translational Medicine 2026;6(4):45 View