Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection

Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection

Abstract Objective To develop a stratified screening tool through machine learning approaches for the Center for Epidemiologic Studies Depression Scale (CES-D-20) while maintaining diagnostic accuracy, addressing the efficiency limitations in large-scale applications. Methods Data were derived from...

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Bibliographic Details
Main Authors: Ruo-Fei Xu, Zhen-Jing Liu, Shunan Ouyang, Qin Dong, Wen-Jing Yan, Dong-Wu Xu
Format: Article
Language:English
Published: BMC 2025-03-01
Series:BMC Psychiatry
Subjects:
Depression screening
Stratified screening
Machine learning
CES-D
Recursive Feature Elimination
Predictive modeling
Online Access:https://doi.org/10.1186/s12888-025-06693-8
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https://doi.org/10.1186/s12888-025-06693-8

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