Machine learning-based prediction of in-hospital mortality in patients with chronic respiratory disease exacerbations
This study developed a prediction model for in-hospital mortality in patients with chronic respiratory disease and demonstrated a relatively high predictive performance. By incorporating environmental factors, such as air pollution exposure levels, the model with the best performance suggested that 365 days of exposure to air pollution was a key risk factor in mortality prediction.
Authors
- Kwang Gi Kim (ORCID: https://orcid.org/0000-0001-9714-6038)
- Young Jae Kim (ORCID: https://orcid.org/0000-0003-0443-0051)
- Seon Min Lee (ORCID: https://orcid.org/0009-0004-8694-2169)
- Seung Yeob Ryu
Institutions
- Gachon University (KR)
- Gachon University Gil Medical Center (KR)
Publication Details
- Journal
- Digital Health
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1177/20552076251326703
- Citations
- 2
- Primary Topic
- Air Quality and Health Impacts
- Type
- article
- Field-Weighted Citation Impact
- 2.40