Predicting depression and unravelling its heterogeneous influences in middle-aged and older people populations: a machine learning approach

Predicting depression and unravelling its heterogeneous influences in middle-aged and older people populations: a machine learning approach

Abstract Background Aging has become a global trend, and depression, as an accompanying issue, poses a significant threat to the health of middle-aged and older adults. Existing studies primarily rely on statistical methods such as logistic regression for small-scale data analysis, while research on...

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Bibliographic Details
Main Authors: Ling Zhang, Ruigang Wei, Jingwen Zhou, Lin Tan, Xiaolong Che, Minqinag Zhang, Xiaoyue Ning, Zhiliang Zhong
Format: Article
Language:English
Published: BMC 2025-04-01
Series:BMC Psychology
Subjects:
Depression symptoms
Machine learning
Deep learning
LSTM
CNN
Longitudinal study
Online Access:https://doi.org/10.1186/s40359-025-02691-3
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