Development and Validation of a Machine Learning‑Based Predictive Model for Assessing the Risk of Comorbid Depression in Patients With Asthma
The XGBoost model effectively predicts the risk of depression in asthma patients, serving as a valuable reference for early clinical identification and intervention.
Authors
- Xin Chen (ORCID: https://orcid.org/0000-0002-6259-2289)
- Jingyi Lin (ORCID: https://orcid.org/0009-0002-9747-6437)
- Yinxu Wang (ORCID: https://orcid.org/0009-0003-2267-9915)
- Yutong Liu (ORCID: https://orcid.org/0009-0004-9263-1869)
- Qiu Nie (ORCID: https://orcid.org/0009-0008-0611-6115)
- Jingjing Liu (ORCID: https://orcid.org/0009-0000-1885-2883)
- Qingsong Ren (ORCID: https://orcid.org/0009-0006-8672-4238)
- Yulei Xie (ORCID: https://orcid.org/0000-0003-1161-5804)
- Wen Li (ORCID: https://orcid.org/0009-0003-7939-7935)
- Xinyu Deng (ORCID: https://orcid.org/0009-0008-7515-0528)
- Ten H. Lai (ORCID: https://orcid.org/0009-0001-3808-8445)
Institutions
- North Sichuan Medical University (CN)
- China Rehabilitation Research Center (CN)
- Suizhou Central Hospital (CN)
- Affiliated Hospital of North Sichuan Medical College (CN)
Publication Details
- Journal
- ALPHA PSYCHIATRY
- Published
- 2025-10-28
- DOI
- https://doi.org/10.31083/ap47754
- Primary Topic
- Asthma and respiratory diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00