Early prediction and identification for severe patients during the pandemic of COVID-19: A severe COVID-19 risk model constructed by multivariate logistic regression analysis-Reference-Cited by-同舟云学术

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Early prediction and identification for severe patients during the pandemic of COVID-19: A severe COVID-19 risk model constructed by multivariate logistic regression analysis

Published:2020-09-04 Issue:2 Volume:10 Page:
ISSN:2047-2978
Container-title:Journal of Global Health
language:en
Short-container-title:

Author:

Hu Haifeng,Du Hong,Li Jing,Wang Yage,Wu Xiaoqing,Wang Chunfu,Zhang Ye,Zhang Gufen,Zhao Yanyan,Kang Wen,Lian Jianqi

Publisher

International Global Health Society

Subject

Public Health, Environmental and Occupational Health,Health Policy

Cited by 36 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predictive Modeling and Analysis of COVID-19 with Machine Learning Techniques;2024 5th International Conference on Image Processing and Capsule Networks (ICIPCN);2024-07-03

2. Development and validation of a prediction model for mortality in critically ill COVID-19 patients;Frontiers in Cellular and Infection Microbiology;2024-06-24

3. Deep learning in public health: Comparative predictive models for COVID-19 case forecasting;PLOS ONE;2024-03-14

4. Associated Biochemical and Hematological Markers in COVID-19 Severity Prediction;Advances in Medicine;2023-10-19

5. Validation of a risk prediction model for COVID-19: the PERIL prospective cohort study;Future Virology;2023-10

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