A Machine Learning Approach for Mortality Prediction in COVID-19 Pneumonia: Development and Evaluation of the Piacenza Score.

Journal: Journal of medical Internet research
Published Date: May 31, 2021

Abstract

BACKGROUND: Several models have been developed to predict mortality in patients with COVID-19 pneumonia, but only a few have demonstrated enough discriminatory capacity. Machine learning algorithms represent a novel approach for the data-driven prediction of clinical outcomes with advantages over statistical modeling.

Authors

  • Geza Halasz
    Department of Cardiology, Guglielmo Da Saliceto Hospital, Piacenza, Italy.
  • Michela Sperti
    PolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Torino, Italy.
  • Matteo Villani
    Anesthesiology and ICU Department, Guglielmo da Saliceto Hospital, Piacenza, Italy.
  • Umberto Michelucci
    TOELT LLC - AI Research and Development, Dubendorf, Switzerland.
  • Piergiuseppe Agostoni
    Centro Cardiologico MonzinoScientific Institute for Research, Hospitalisation and Health Care (IRCCS)MilanItaly; Cardiovascular Section, Department of Clinical Sciences and Community HealthUniversity of MilanMilanItaly.
  • Andrea Biagi
    Department of Cardiology, Guglielmo Da Saliceto Hospital, Piacenza, Italy.
  • Luca Rossi
    Dipartimento di Ingegneria dell'Informazione (DII), Universitá Politecnica delle Marche, Ancona, Italy.
  • Andrea Botti
    Department of Clinical and Experimental Medicine, University of Parma, Parma, Italy.
  • Chiara Mari
    Department of Clinical and Experimental Medicine, University of Parma, Parma, Italy.
  • Marco Maccarini
    Dalle Molle Institute for Artificial Intelligence, Università della Svizzera italiana/Scuola universitaria professionale della Svizzera italiana, Lugano, Switzerland.
  • Filippo Pura
    Dalle Molle Institute for Artificial Intelligence, Università della Svizzera italiana/Scuola universitaria professionale della Svizzera italiana, Lugano, Switzerland.
  • Loris Roveda
    Dalle Molle Institute for Artificial Intelligence, Università della Svizzera italiana/Scuola universitaria professionale della Svizzera italiana, Lugano, Switzerland.
  • Alessia Nardecchia
    Istituto Istruzione Superiore, Casalpusterlengo, Italy.
  • Emanuele Mottola
    7HC SRL, Rome, Italy.
  • Massimo Nolli
    Anesthesiology and ICU Department, Guglielmo da Saliceto Hospital, Piacenza, Italy.
  • Elisabetta Salvioni
    Centro Cardiologico Monzino Scientific Institute for Research, Hospitalisation and Health Care (IRCCS) Milan Italy.
  • Massimo Mapelli
    Centro Cardiologico Monzino IRCCS, Milano, Italy; Department of Clinical Sciences and Community Health, Cardiovascular Section, University of Milano, Milano, Italy.
  • Marco Agostino Deriu
    Polito BIO Med Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy.
  • Dario Piga
    Dalle Molle Institute for Artificial Intelligence, Università della Svizzera italiana/Scuola universitaria professionale della Svizzera italiana, Lugano, Switzerland.
  • Massimo Piepoli
    Department of Cardiology, Guglielmo Da Saliceto Hospital, Piacenza, Italy.

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