Predicting non-suicidal self-injury among Chinese adolescents: The application of ten algorithms of machine learning

The ensemble machine learning algorithm showed promising results predicting NSSI among adolescents. Such algorithms should be recommended for future NSSI research to enhance predictive accuracy. Identification of important features in NSSI prediction can help develop screening protocols and lay a foundation for clinical diagnosis and intervention in adolescent populations.

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Publication Details

Journal
Heliyon
Published
2024-09-01
DOI
https://doi.org/10.1016/j.heliyon.2024.e37723
Citations
5
Primary Topic
Suicide and Self-Harm Studies
Type
article
Field-Weighted Citation Impact
3.20

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article

Predicting non-suicidal self-injury among Chinese adolescents: The application of ten algorithms of machine learning

Wei Chen, Shiyin Xiao, Yujing Gao
5 citations
Heliyon
Suicide and Self-Harm Studies
3.20
article

Predicting non-suicidal self-injury among Chinese adolescents: The application of ten algorithms of machine learning

Wei Chen, Shiyin Xiao, Yujing Gao
article en
5 citations

Abstract

The ensemble machine learning algorithm showed promising results predicting NSSI among adolescents. Such algorithms should be recommended for future NSSI research to enhance predictive accuracy. Identification of important features in NSSI prediction can help develop screening protocols and lay a foundation for clinical diagnosis and intervention in adolescent populations.

HeliyonVol. 10(18)
Guizhou Normal University (CN)
Jilin Office of Philosophy and Social Science
Gender equality
Openalex Percentile: Top 8%
Suicide and Self-Harm Studies
3.20
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