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

ABSTRACT:

Background

Biological age (BA) is increasingly recognized as a valuable alternative to chronological age (CA) for assessing an individual's health and aging status. However, existing models are based on limited clinical parameters and have not thoroughly integrated morbidity and mortality data.

Objective

This study aimed to develop and validate a novel transformer-based model, referred to as the BA - CA gap model, for BA estimation that incorporates morbidity and mortality information to improve predictive accuracy and enhance clinical use in the early identification of the risk of age-related diseases.

Methods

We retrospectively analyzed data from 151,281 adults aged 18 years or older who underwent routine health checkups between 2003 and 2020. Participants were clas

SUBMITTER: Moon SE 

PROVIDER: S-EPMC12422742 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature