Identification of depressive symptoms in adolescents using machine learning combining childhood and adolescence features
This study demonstrates the correlation between adolescence depressive symptoms and specific factors from both childhood and adolescence, as well as the potential of ML to predict it. These findings may serve as a reference for future intervention studies.
Authors
- Hui Wu (ORCID: https://orcid.org/0000-0003-4907-3625)
- Zihe Zhang (ORCID: https://orcid.org/0000-0001-6571-0159)
- Wei Liu (ORCID: https://orcid.org/0000-0002-9302-8170)
- Ping Li (ORCID: https://orcid.org/0000-0002-4926-3835)
- Xinzhu Liu (ORCID: https://orcid.org/0000-0002-6447-2926)
- Shu Li (ORCID: https://orcid.org/0000-0002-6602-5126)
- Rui Cang
Institutions
- Shenyang Medical College (CN)
- First Hospital of China Medical University (CN)
- China Medical University (CN)
Publication Details
- Journal
- BMC Public Health
- Published
- 2025-01-22
- DOI
- https://doi.org/10.1186/s12889-025-21506-z
- Citations
- 1
- Primary Topic
- Child and Adolescent Psychosocial and Emotional Development
- Type
- article
- Field-Weighted Citation Impact
- 2.31