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

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Bibliographic Details
Title:	Uncovering Clinical Risk Factors and Predicting Severe COVID-19 Cases Using UK Biobank Data: Machine Learning Approach.
Authors:	Wong KC; School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China., Xiang Y; School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China., Yin L; School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China., So HC; School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China.; KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research of Common Diseases, Kunming Institute of Zoology and The Chinese University of Hong Kong, Kunming, China.; CUHK Shenzhen Research Institute, Shenzhen, China.; Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong, China.; Margaret K.L. Cheung Research Centre for Management of Parkinsonism, The Chinese University of Hong Kong, Hong Kong, China.; Brain and Mind Institute, The Chinese University of Hong Kong, Hong Kong, China.; Hong Kong Branch of the Chinese Academy of Sciences Center for Excellence in Animal Evolution and Genetics, The Chinese University of Hong Kong, Hong Kong, China.
Source:	JMIR public health and surveillance [JMIR Public Health Surveill] 2021 Sep 30; Vol. 7 (9), pp. e29544. Date of Electronic Publication: 2021 Sep 30.
Publication Type:	Journal Article
Journal Info:	Publisher: JMIR Publications Country of Publication: Canada NLM ID: 101669345 Publication Model: Electronic Cited Medium: Internet ISSN: 2369-2960 (Electronic) Linking ISSN: 23692960 NLM ISO Abbreviation: JMIR Public Health Surveill Subsets: MEDLINE
Database:	MEDLINE Ultimate

Description
ISSN:	2369-2960
DOI:	10.2196/29544