This paper is in the following e-collection/theme issue:

Statistical Methods for Surveillance and Population Health (156) JMIR Theme Issue: COVID-19 Special Issue (2452) Machine Learning (1465) Innovative Methods in Public Health and Surveillance (332) Artificial Intelligence (1371) Infectious Diseases (non-STD/STI) (1575) Surveillance Systems (462) Public Health Informatics (93) Outbreak and Pandemic Preparedness and Management (1727)

Published on in Vol 7, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29544, first published .
Uncovering Clinical Risk Factors and Predicting Severe COVID-19 Cases Using UK Biobank Data: Machine Learning Approach

Uncovering Clinical Risk Factors and Predicting Severe COVID-19 Cases Using UK Biobank Data: Machine Learning Approach

Uncovering Clinical Risk Factors and Predicting Severe COVID-19 Cases Using UK Biobank Data: Machine Learning Approach

Authors of this article:

Kenneth Chi-Yin Wong1 Author Orcid Image ;   Yong Xiang1 Author Orcid Image ;   Liangying Yin1 Author Orcid Image ;   Hon-Cheong So1, 2, 3, 4, 5, 6, 7 Author Orcid Image
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