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A Machine Learning Approach to Predict the Rehabilitation Outcome in Convalescent COVID-19 Patients.
Adamo, Sarah; Ambrosino, Pasquale; Ricciardi, Carlo; Accardo, Mariasofia; Mosella, Marco; Cesarelli, Mario; d'Addio, Giovanni; Maniscalco, Mauro.
Afiliação
  • Adamo S; Istituti Clinici Scientifici Maugeri IRCCS, Bioengineering Unit of Telese Terme Institute, 82037 Telese Terme, Italy.
  • Ambrosino P; Department of Information Technology and Electrical Engineering, University of Naples "Federico II", 80125 Naples, Italy.
  • Ricciardi C; Istituti Clinici Scientifici Maugeri IRCCS, Cardiac Rehabilitation Unit of Telese Terme Institute, 82037 Telese Terme, Italy.
  • Accardo M; Istituti Clinici Scientifici Maugeri IRCCS, Bioengineering Unit of Telese Terme Institute, 82037 Telese Terme, Italy.
  • Mosella M; Department of Information Technology and Electrical Engineering, University of Naples "Federico II", 80125 Naples, Italy.
  • Cesarelli M; Istituti Clinici Scientifici Maugeri IRCCS, Pulmonary Rehabilitation Unit of Telese Terme Institute, 82037 Telese Terme, Italy.
  • d'Addio G; Istituti Clinici Scientifici Maugeri IRCCS, Pulmonary Rehabilitation Unit of Telese Terme Institute, 82037 Telese Terme, Italy.
  • Maniscalco M; Istituti Clinici Scientifici Maugeri IRCCS, Bioengineering Unit of Telese Terme Institute, 82037 Telese Terme, Italy.
J Pers Med ; 12(3)2022 Feb 22.
Article em En | MEDLINE | ID: mdl-35330328
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: 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: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article