Clinical characteristics and prediction model of re-positive nucleic acid tests among Omicron infections by machine learning: a real-world study of 35,488 cases
Higher TR risk was found in infected cases who were underage or with underlying diseases; vaccine brand and inoculation status were not significantly associated with TR. KNN was the most effective machine learning model to predict TR occurrence in isolation.
Authors
- Liang Tan (ORCID: https://orcid.org/0000-0002-9014-5371)
- Ying Cao (ORCID: https://orcid.org/0000-0001-7290-0655)
- Junsheng Qi (ORCID: https://orcid.org/0000-0001-9013-5467)
- Yazhou Wu (ORCID: https://orcid.org/0000-0002-9521-2940)
- Tianhua Yao
- Rui Zhang (ORCID: https://orcid.org/0000-0002-5399-7057)
- Zhiqiang Chen (ORCID: https://orcid.org/0000-0003-0242-6577)
- Zhixiong Zhang (ORCID: https://orcid.org/0000-0001-6542-7257)
- Changlin Yin
- Ronghao Li (ORCID: https://orcid.org/0009-0009-7174-2638)
Institutions
- Army Medical University (CN)
- Southwest Hospital (CN)
Publication Details
- Journal
- BMC Infectious Diseases
- Published
- 2024-12-18
- DOI
- https://doi.org/10.1186/s12879-024-10297-0
- Primary Topic
- SARS-CoV-2 detection and testing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Chongqing
- Southwest Hospital
- Centre Scientifique et Technique du Bâtiment