Development and validation of deep learning- and ensemble learning-based biological ages in the NHANES study

Development and validation of deep learning- and ensemble learning-based biological ages in the NHANES study

IntroductionConventional machine learning (ML) approaches for constructing biological age (BA) have predominantly relied on blood-based markers, limiting their scope. This study aims to develop and validate novel ML-based BA models using a comprehensive set of clinical, behavioral, and socioeconomic...

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Bibliographic Details
Main Authors: Yushu Huang, Xifan Yang, Qi Wang, Adila Abula, Yue Dong, Wenyuan Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Aging Neuroscience
Subjects:
aging
biological age
machine learning
deep learning
deep neural networks
Online Access:https://www.frontiersin.org/articles/10.3389/fnagi.2025.1532884/full
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