Machine learning for identifying risk of death in patients with severe fever with thrombocytopenia syndrome
Using ML can be a good way to identify high risk individuals in SFTS patients. We can use this model to identify patients at high risk of death early in their admission and manage them intensively at an early stage.
Authors
- Zihao You
- Zhaoru Zhang (ORCID: https://orcid.org/0000-0001-6125-8660)
- Qionghan He
- Jiale Guo
- Qiuping Dong
Institutions
- Anhui Medical University (CN)
- Chaohu Hospital of Anhui Medical University (CN)
- Anhui Mental Health Center (CN)
- Hefei Infectious Disease Hospital (CN)
Publication Details
- Journal
- Frontiers in Microbiology
- Published
- 2024-09-13
- DOI
- https://doi.org/10.3389/fmicb.2024.1458670
- Citations
- 6
- Primary Topic
- Viral Infections and Vectors
- Type
- article
- Field-Weighted Citation Impact
- 2.33