AI-Based Hematological Age Predictors and the Association Between Biological Age Acceleration and Type 2 Diabetes Mellitus - Chongqing Municipality, China, 2015-2021.

Zhe Yin, Yingnan Song, Junhui Zhang, Qiaoyun Dai, Xinyuan Zhang, Xueying Yang, Na Nie, Cuixia Chen, Zongfu Cao, Xu Ma

National Human Genetic Resources Center, National Research Institute for Family Planning, Beijing, China. · pubmed

Abstract

Biological age (BA) can represent the actual state of human aging more accurately than chronological age (CA).

The following analysis is generated by AI and may contain errors. It is separate from the authors’ abstract and is not peer review.

Research summary

The paper investigates biological age predictors and their association with type 2 diabetes mellitus, which is relevant to understanding aging processes. However, it primarily focuses on a specific disease rather than addressing the root causes of aging or lifespan extension. The findings may contribute to the field but are not groundbreaking or transformative, hence the low impact score.

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