Prediction of non-suicidal self-injury (NSSI) among rural Chinese junior high school students: a machine learning approach
This study focused on Chinese children and adolescents in rural areas and demonstrated the potential of using machine learning approaches in predicting NSSI. Our research complements the application of machine learning methods to psychiatric and psychological problems.
Authors
- Cody Abbey (ORCID: https://orcid.org/0000-0002-1281-5472)
- Jingwen Jin (ORCID: https://orcid.org/0000-0001-9227-6837)
- Wenjian Xu (ORCID: https://orcid.org/0000-0002-4304-3479)
- Yonghua Cui
- Dongdong Zhang (ORCID: https://orcid.org/0000-0002-0091-1803)
- Weitong Guo (ORCID: https://orcid.org/0009-0004-1664-1424)
- Ying Li (ORCID: https://orcid.org/0000-0003-4571-2637)
- Jintong Liu (ORCID: https://orcid.org/0000-0002-1100-0378)
- Hui Xu
- Zhongliang Jiang
Institutions
- Shandong University (CN)
- Capital Medical University (CN)
- Shandong Mental Health Center (CN)
- Beijing Children’s Hospital (CN)
- University of Hong Kong (HK)
- Stanford University (US)
Publication Details
- Journal
- Annals of General Psychiatry
- Published
- 2024-12-06
- DOI
- https://doi.org/10.1186/s12991-024-00534-w
- Citations
- 9
- Primary Topic
- Suicide and Self-Harm Studies
- Type
- article
- Field-Weighted Citation Impact
- 5.75
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Beijing Municipality