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COVID-19 machine learning model predicts outcomes in older patients from various European countries, between pandemic waves, and in a cohort of Asian, African, and American patients.
Mamandipoor, Behrooz; Bruno, Raphael Romano; Wernly, Bernhard; Wolff, Georg; Fjølner, Jesper; Artigas, Antonio; Pinto, Bernardo Bollen; Schefold, Joerg C; Kelm, Malte; Beil, Michael; Sigal, Sviri; Leaver, Susannah; De Lange, Dylan W; Guidet, Bertrand; Flaatten, Hans; Szczeklik, Wojciech; Jung, Christian; Osmani, Venet.
Afiliación
  • Mamandipoor B; Digital Health Centre, Fondazione Bruno Kessler Research Institute, Trento, Italy.
  • Bruno RR; Heinrich-Heine-University Duesseldorf, Medical Faculty, Department of Cardiology, Pulmonology and Vascular Medicine, Duesseldorf, Germany.
  • Wernly B; Department of Internal Medicine, General Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University Salzburg, 5020 Salzburg, Austria.
  • Wolff G; Institute of General Practice, Family Medicine and Preventive Medicine, Paracelsus Medical University, Salzburg, Austria.
  • Fjølner J; Heinrich-Heine-University Duesseldorf, Medical Faculty, Department of Cardiology, Pulmonology and Vascular Medicine, Duesseldorf, Germany.
  • Artigas A; Department of Anaesthesia and Intensive Care, Viborg Regional Hospital, Viborg, Denmark.
  • Pinto BB; Department of Intensive Care Medicine, CIBER Enfermedades Respiratorias, Corporacion Sanitaria Universitaria Parc Tauli, Autonomous University of Barcelona, Sabadell, Spain.
  • Schefold JC; Department of Acute Medicine, Geneva University Hospitals, Geneva, Switzerland.
  • Kelm M; Department of Intensive Care Medicine, Inselspital, Universitätsspital, University of Bern, Bern, Switzerland.
  • Beil M; Heinrich-Heine-University Duesseldorf, Medical Faculty, Department of Cardiology, Pulmonology and Vascular Medicine, Duesseldorf, Germany.
  • Sigal S; Dept. of Medical Intensive Care, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Israel.
  • Leaver S; Dept. of Medical Intensive Care, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Israel.
  • De Lange DW; General Intensive care, St George's University Hospitals NHS Foundation trust, London, United Kingdom.
  • Guidet B; Department of Intensive Care Medicine, University Medical Center, University Utrecht, the Netherlands.
  • Flaatten H; Sorbonne Universités, UPMC Univ Paris 06, INSERM, UMR_S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Equipe: épidémiologie hospitalière qualité et organisation des soins, F-75012, Paris, France.
  • Szczeklik W; Assistance Publique-Hôpitaux de Paris, Hôpital Saint-Antoine, service de réanimation médicale, Paris, France.
  • Jung C; Department of Clinical Medicine, University of Bergen, Department of Anaesthesia and Intensive Care, Haukeland University Hospital, Bergen, Norway.
  • Osmani V; Jagiellonian University Medical College, Center for Intensive Care and Perioperative Medicine, Krakow, Poland.
PLOS Digit Health ; 1(11): e0000136, 2022 Nov.
Article en En | MEDLINE | ID: mdl-36812571
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLOS Digit Health Año: 2022 Tipo del documento: Article País de afiliación: Italia
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLOS Digit Health Año: 2022 Tipo del documento: Article País de afiliación: Italia