Machine learning models for preventative mobile health asthma control
As proved by the XGBoost model, predicting asthma triggers can be a viable option for asthma control using machine learning. In addition, the actionable information of triggers, allows patients to make behavior changes. However there will still need to be work testing the system in a mobile health system.
Authors
- Alan S.L. Wong (ORCID: https://orcid.org/0000-0003-1790-3233)
Institutions
- Wake Technical Community College (US)
Publication Details
- Journal
- Journal of Asthma
- Published
- 2025-01-16
- DOI
- https://doi.org/10.1080/02770903.2025.2453812
- Citations
- 2
- Primary Topic
- Asthma and respiratory diseases
- Type
- article
- Field-Weighted Citation Impact
- 2.33