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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https://doi.org/10.1186/s40345-024-00365-4

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