Predicting 30-day in-hospital mortality in ICU asthma patients: a retrospective machine learning study with external validation
We developed and externally validated a robust prediction model for 30-day mortality in ICU patients with asthma. The model offers strong performance, interpretability, and clinical utility, supporting its use for real-time risk stratification and decision-making in critical care settings.
Authors
- Jiaolin Sun
- Yuanshuo Ge (ORCID: https://orcid.org/0000-0003-0998-4870)
- Wenwen Ji
- Tingting Liu (ORCID: https://orcid.org/0000-0001-6396-7225)
- Yaxin Zhang (ORCID: https://orcid.org/0000-0002-9533-1472)
- Guangdong Wang (ORCID: https://orcid.org/0000-0001-7237-3517)
Institutions
- Fujian Medical University (CN)
- Shanxi Medical University (CN)
- Xiamen University (CN)
- First Affiliated Hospital of Xi'an Jiaotong University (CN)
- Shanxi Provincial People’s Hospital (CN)
- Jinzhou Medical University (CN)
Publication Details
- Journal
- BMC Pulmonary Medicine
- Published
- 2025-08-12
- DOI
- https://doi.org/10.1186/s12890-025-03881-w
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Massachusetts Institute of Technology