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Predicting oxygen requirements in patients with coronavirus disease 2019 using an artificial intelligence-clinician model based on local non-image data.
Muto, Reiko; Fukuta, Shigeki; Watanabe, Tetsuo; Shindo, Yuichiro; Kanemitsu, Yoshihiro; Kajikawa, Shigehisa; Yonezawa, Toshiyuki; Inoue, Takahiro; Ichihashi, Takuji; Shiratori, Yoshimune; Maruyama, Shoichi.
Afiliação
  • Muto R; Department of Nephrology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Fukuta S; Department of Internal Medicine, Aichi Prefectural Aichi Hospital, Okazaki, Japan.
  • Watanabe T; Department of Molecular Medicine and Metabolism, Research Institute of Environmental Medicine, Nagoya University, Nagoya, Japan.
  • Shindo Y; Artificial Intelligence Laboratory, Fujitsu Limited, Kawasaki, Japan.
  • Kanemitsu Y; DX Platform Business Unit, Fujitsu Limited, Nagoya, Japan.
  • Kajikawa S; Department of Internal Medicine, Aichi Prefectural Aichi Hospital, Okazaki, Japan.
  • Yonezawa T; Department of Respiratory Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Inoue T; Department of Internal Medicine, Aichi Prefectural Aichi Hospital, Okazaki, Japan.
  • Ichihashi T; Department of Respiratory Medicine, Allergy and Clinical Immunology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.
  • Shiratori Y; Department of Internal Medicine, Aichi Prefectural Aichi Hospital, Okazaki, Japan.
  • Maruyama S; Department of Respiratory Medicine and Allergology, Aichi Medical University Hospital, Nagakute, Japan.
Front Med (Lausanne) ; 9: 1042067, 2022.
Article em En | MEDLINE | ID: mdl-36530899
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article