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A machine learning approach to characterize patients with asthma exacerbation attending an acute care setting.
D'Amato, Maria; Ambrosino, Pasquale; Simioli, Francesca; Adamo, Sarah; Stanziola, Anna Agnese; D'Addio, Giovanni; Molino, Antonio; Maniscalco, Mauro.
Afiliação
  • D'Amato M; Department of Respiratory Medicine, Federico II University, Naples, Italy. Electronic address: marielladam@hotmail.it.
  • Ambrosino P; Istituti Clinici Scientifici Maugeri IRCCS, Cardiac Rehabilitation Unit of Telese Terme Institute, Telese Terme, Italy.
  • Simioli F; Department of Respiratory Medicine, Federico II University, Naples, Italy.
  • Adamo S; Department of Information Technology and Electrical Engineering, University of Naples "Federico II", Napoli, Italy.
  • Stanziola AA; Department of Respiratory Medicine, Federico II University, Naples, Italy.
  • D'Addio G; Istituti Clinici Scientifici Maugeri IRCCS, Bioengineering Unit of Telese Terme Institute, Telese Terme, Italy.
  • Molino A; Department of Respiratory Medicine, Federico II University, Naples, Italy.
  • Maniscalco M; Department of Respiratory Medicine, Federico II University, Naples, Italy; Istituti Clinici Scientifici Maugeri IRCCS, Pulmonary Rehabilitation Unit of Telese Terme Institute, Telese Terme, Italy. Electronic address: mauro.maniscalco@icsmaugeri.it.
Eur J Intern Med ; 104: 66-72, 2022 Oct.
Article em En | MEDLINE | ID: mdl-35922367
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Asma Tipo de estudo: Prognostic_studies Limite: Female / Humans / Male 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 Assunto principal: Asma Tipo de estudo: Prognostic_studies Limite: Female / Humans / Male Idioma: En Ano de publicação: 2022 Tipo de documento: Article