Identification of depressive symptoms in adolescents using machine learning combining childhood and adolescence features

Identification of depressive symptoms in adolescents using machine learning combining childhood and adolescence features

Abstract Background Depressive symptoms in adolescents can significantly affect their daily lives and pose risks to their future development. These symptoms may be linked to various factors experienced during both childhood and adolescence. Machine learning (ML) has attracted substantial attention i...

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Bibliographic Details
Main Authors: Xinzhu Liu, Rui Cang, Zihe Zhang, Ping Li, Hui Wu, Wei Liu, Shu Li
Format: Article
Language:English
Published: BMC 2025-01-01
Series:BMC Public Health
Subjects:
Child-adolescent model
Depression
Adolescence
Childhood
Online Access:https://doi.org/10.1186/s12889-025-21506-z
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