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

Seong-Eun Moon, Ji Won Yoon, Jae Hyun Bae, Shinyoung Joo, Yoo Hyung Kim, Bon Hyang Lee, Seokho Yoon, Haanju Yoo, Young Min Cho

NAVER AI Lab, Seongnam, Republic of Korea.NAVER AI Lab, Seongnam, Republic of Korea. · pubmed

Paper

Abstract

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.

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Research summary

The paper claims to develop a model for estimating biological age by integrating morbidity and mortality data using deep learning. This research is relevant as it seeks to improve the understanding of biological age, which is crucial for assessing health and aging, potentially leading to better interventions in longevity and age-related diseases.

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