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

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

Abstract Background During the Omicron BA.2 variant outbreak in Shanghai, China, from April to May 2022, PCR nucleic acid test re-positivity (TR) occurred frequently, yet the risk factors and predictive models for TR remain unclear. This study aims to identify the factors influencing Omicron TR and...

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Bibliographic Details
Main Authors: Ying Cao, Tianhua Yao, Ronghao Li, Liang Tan, Zhixiong Zhang, Junsheng Qi, Rui Zhang, Yazhou Wu, Zhiqiang Chen, Changlin Yin
Format: Article
Language:English
Published: BMC 2024-12-01
Series:BMC Infectious Diseases
Subjects:
Re-positive
Omicron
Decision-making
Machine learning
COVID-19
Online Access:https://doi.org/10.1186/s12879-024-10297-0
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https://doi.org/10.1186/s12879-024-10297-0

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