From dry eye to depression: a machine learning-based framework for predicting adolescent mental health
Integrating ocular health with psychosocial factors enhances machine-learning prediction of adolescent depression and may support earlier, school-based identification and referral. Given the low-cost, questionnaire-based inputs and favorable calibration, this approach shows promise for population screening and targeted prevention, pending external validation and prospective testing.
Authors
- Zijuan Ma (ORCID: https://orcid.org/0000-0003-2260-1862)
- Xiao Liu (ORCID: https://orcid.org/0000-0002-5363-6331)
- Xuejiao Liu (ORCID: https://orcid.org/0000-0003-1821-2864)
- Ying Jie (ORCID: https://orcid.org/0000-0003-4003-2579)
- Ying Liu (ORCID: https://orcid.org/0000-0002-6540-0473)
- Le Han (ORCID: https://orcid.org/0000-0003-2985-3165)
- Lei Tian (ORCID: https://orcid.org/0000-0002-7216-5352)
- Kai Cao (ORCID: https://orcid.org/0000-0002-9546-1613)
- Yunshuang Liu
- Peng Xian (ORCID: https://orcid.org/0000-0001-7602-0524)
- Li Ren
- Shijing Deng
- Yue Chang
Institutions
- Beijing Tongren Hospital (CN)
- Capital Medical University (CN)
- Beijing Center for Disease Prevention and Control (CN)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2025-11-06
- DOI
- https://doi.org/10.1186/s12911-025-03246-7
- Primary Topic
- Ophthalmology and Visual Impairment Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00