Identification of critical SARS-CoV-2 amino acids associated with COVID-19 hospitalization rate using machine learning and statistical modeling: An observational study in the United States.

Liang, Jingbo; Ding, Zhaojun; Liu, Kunmeng

Liang, Jingbo; Ding, Zhaojun; Liu, Kunmeng.

Afiliación

Liang J; Department of Biomedical Sciences, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong SAR, China. Electronic address: jliang63-c@my.cityu.edu.hk.
Ding Z; Department of Biomedical Sciences, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong SAR, China.
Liu K; Center for Medical Artificial Intelligence, Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao, China.

Infect Genet Evol ; 113: 105480, 2023 09.

Article en En | MEDLINE | ID: mdl-37437768

Asunto(s)

COVID-19; SARS-CoV-2; Estados Unidos/epidemiología; Humanos; SARS-CoV-2/genética; COVID-19/epidemiología; Aminoácidos; Pandemias; Aprendizaje Automático; Hospitalización

Palabras clave

COVID-19; Case hospitalization ratio; SARS-CoV-2 amino acid mutation

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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: SARS-CoV-2 / COVID-19 Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Infect Genet Evol Asunto de la revista: BIOLOGIA / DOENCAS TRANSMISSIVEIS / GENETICA Año: 2023 Tipo del documento: Article

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