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

Data Science (357) Aging with Chronic Disease (177) Decision Support for Health Professionals (1539) Machine Learning (2076) Tools, Programs and Algorithms (376) Artificial Intelligence (2129) Clinical Information and Decision Making (1915) New Methods (1134)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71592, first published .
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

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
Article Authors Cited by Tweetations (1) Metrics

Seong-Eun Moon   1 * , PhD ;   Ji Won Yoon   2, 3 * , MD, PhD ;   Jae Hyun Bae   3, 4 * , MD, PhD ;   Shinyoung Joo   1 , MS ;   Yoo Hyung Kim   4 , MD, PhD ;   Bon Hyang Lee   4 , MBBS ;   Seokho Yoon   5 , PhD ;   Haanju Yoo   1 * , PhD ;   Young Min Cho   3, 4 * , MD, PhD

1 NAVER AI Lab, Seongnam, Republic of Korea

2 Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Republic of Korea

3 Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea

4 Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea

5 DaNaA Data, Seoul, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Young Min Cho, MD, PhD
  • Department of Internal Medicine
  • Seoul National University College of Medicine
  • 101 Daehak-ro, Jongno-gu
  • Seoul 03080
  • Republic of Korea
  • Phone: 82 0220721965
  • Email: ymchomd@snu.ac.kr