Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort
We developed an interpretable, deployable tool for early triage of hymenopteran sting patients in tropical settings. Emergency integration may improve clinical decisions and outcomes.
Authors
- Feng Han (ORCID: https://orcid.org/0009-0002-7449-6750)
- Yuanshui Liu
- Huamei Li (ORCID: https://orcid.org/0009-0009-0112-0972)
- Liming Liang (ORCID: https://orcid.org/0000-0001-8261-3174)
- Dongchuan Xu
- Wang Liao (ORCID: https://orcid.org/0000-0002-6187-0443)
- Xiaofang Chen (ORCID: https://orcid.org/0009-0003-1521-4431)
- Ping He (ORCID: https://orcid.org/0009-0005-5566-8993)
- Yanhong Ouyang
- Lijiao Ye
Institutions
- Hainan Center for Disease Control & Prevention (CN)
- Hainan General Hospital (CN)
- Hainan Medical University (CN)
Publication Details
- Journal
- Frontiers in Public Health
- Published
- 2025-10-28
- DOI
- https://doi.org/10.3389/fpubh.2025.1664606
- Primary Topic
- Food Allergy and Anaphylaxis Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Hainan Medical University