The prediction of self-harm behaviors in young adults with multi-modal data: an XGBoost approach

The prediction of self-harm behaviors in young adults with multi-modal data: an XGBoost approach

Objectives: To enhance the ability of predicting self-harm behaviors through multidimensional data and machine learning methods, and provide a foundation for future comprehensive interventions. Methods: One hundred and twelve young adults aged 18-22 years with self-harm behaviors participated in thi...

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Bibliographic Details
Main Authors: Xiao-Ming Xu, Yang S. Liu, Su Hong, Chuan Liu, Jun Cao, Xiao-Rong Chen, Zhen Lv, Bo Cao, Heng-Guang Wang, Wo Wang, Ming Ai, Li Kuang
Format: Article
Language:English
Published: Elsevier 2024-04-01
Series:Journal of Affective Disorders Reports
Subjects:
Self-harm
Young adults
XGBoost
Single nucleotide polymorphism
Online Access:http://www.sciencedirect.com/science/article/pii/S2666915324000088

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http://www.sciencedirect.com/science/article/pii/S2666915324000088

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