Machine learning-driven simplification of the hypomania checklist-32 for adolescent: a feature selection approach

Machine learning-driven simplification of the hypomania checklist-32 for adolescent: a feature selection approach

Abstract Background The Hypomania Checklist-32 is widely used to screen for bipolar disorder, but its length can be challenging for adolescents with manic symptoms. This study aimed to develop a shortened version of the HCL-32 tailored for adolescents using machine learning techniques. Methods Data...

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Bibliographic Details
Main Authors:	Guanghui Shen, Haoran Chen, Xinwu Ye, Xiaodong Xue, Shusi Tang
Format:	Article
Language:	English
Published:	SpringerOpen 2024-12-01
Series:	International Journal of Bipolar Disorders
Subjects:	Feature selection Random forest Gradient boosting machine Scale reduction Manic symptoms
Online Access:	https://doi.org/10.1186/s40345-024-00365-4
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