Development of a COVID-19 early risk assessment system based on multiple machine learning algorithms and routine blood tests: a real-world study
This novel risk assessment system is highly accurate in predicting the prognosis of patients with COVID-19, especially elderly patients with COVID-19, and can be well applied within the PPPM framework. Our ML model facilitates stratified patient management, meanwhile promoting the optimal use of healthcare resources.
Authors
- Qiangqiang Qin (ORCID: https://orcid.org/0000-0003-2865-1617)
- Qingxuan Li (ORCID: https://orcid.org/0000-0001-5163-7958)
- Mingyan Peng
- Shuang Wu (ORCID: https://orcid.org/0009-0006-0842-5195)
- Wen Gu (ORCID: https://orcid.org/0000-0003-1414-0605)
- Xuejun Guo (ORCID: https://orcid.org/0000-0003-4842-8797)
- Haiyang Yu
- Xue Xu (ORCID: https://orcid.org/0000-0002-8328-5827)
- Guiyin Zhu
Institutions
- Anhui Medical University (CN)
- XinHua Hospital (CN)
- Second Affiliated Hospital of Jilin University (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2024-09-30
- DOI
- https://doi.org/10.3389/fimmu.2024.1430899
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Peking University