Prognostic Factors for Covid-19 on Admission Profile and Air Pollutants.

Sato, Kikue; Furukawa, Taiki; Yamashita, Satoshi; Kobayashi, Daisuke; Oyama, Shintaro; Shiratori, Yoshimune

Sato, Kikue; Furukawa, Taiki; Yamashita, Satoshi; Kobayashi, Daisuke; Oyama, Shintaro; Shiratori, Yoshimune.

Affiliation

Sato K; Nagoya University Hospital Medical IT Center, Nagoya University, Nagoya, Japan.
Furukawa T; Nagoya University Hospital Medical IT Center, Nagoya University, Nagoya, Japan.
Yamashita S; Nagoya University Hospital Medical IT Center, Nagoya University, Nagoya, Japan.
Kobayashi D; Graduate School Medicine/School of Public Health Department of Health Economics and Quality Management, Kyoto University, Kyoto, Japan.
Oyama S; Innovative Research Center for Preventive Medical Engineering, Nagoya University, Nagoya, Japan.
Shiratori Y; Nagoya University Hospital Medical IT Center, Nagoya University, Nagoya, Japan.

Stud Health Technol Inform ; 302: 901-902, 2023 May 18.

Article de En | MEDLINE | ID: mdl-37203529

Sujet(s)
Mots clés

Air Pollution Exposure; Covid-19; Machine Learning; Prognostic Factors

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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Fibrillation auriculaire / Polluants atmosphériques / Pollution de l'air / COVID-19 Type d'étude: Prognostic_studies / Risk_factors_studies Limites: Humans / Infant Langue: En Journal: Stud Health Technol Inform Sujet du journal: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Année: 2023 Type de document: Article Pays d'affiliation: Japon Pays de publication: Pays-Bas

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