This paper is in the following e-collection/theme issue:

JMIR Theme Issue: COVID-19 Special Issue (2092) Artificial Intelligence (668) Machine Learning (1008) Clinical Information and Decision Making (906) Infectious Diseases (non-STD/STI) (1224) Outbreak and Pandemic Preparedness and Management (1456) Decision Support for Health Professionals (737)

Published on in Vol 23 , No 5 (2021) :May

Preprints (earlier versions) of this paper are available at , first published .
A Machine Learning Approach for Mortality Prediction in COVID-19 Pneumonia: Development and Evaluation of the Piacenza Score

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

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

Authors of this article:

Geza Halasz 1 Author Orcid Image ;   Michela Sperti 2 Author Orcid Image ;   Matteo Villani 3 Author Orcid Image ;   Umberto Michelucci 4 Author Orcid Image ;   Piergiuseppe Agostoni 5 Author Orcid Image ;   Andrea Biagi 1 Author Orcid Image ;   Luca Rossi 1 Author Orcid Image ;   Andrea Botti 6 Author Orcid Image ;   Chiara Mari 6 Author Orcid Image ;   Marco Maccarini 7 Author Orcid Image ;   Filippo Pura 7 Author Orcid Image ;   Loris Roveda 7 Author Orcid Image ;   Alessia Nardecchia 8 Author Orcid Image ;   Emanuele Mottola 9 Author Orcid Image ;   Massimo Nolli 3 Author Orcid Image ;   Elisabetta Salvioni 5 Author Orcid Image ;   Massimo Mapelli 5 Author Orcid Image ;   Marco Agostino Deriu 2 Author Orcid Image ;   Dario Piga 7 Author Orcid Image ;   Massimo Piepoli 1 Author Orcid Image
Article Authors Cited by (19) Tweetations (2) Metrics
Geza Halasz 1 * , MD ;   Michela Sperti 2 * , PhD ;   Matteo Villani 3 , MD ;   Umberto Michelucci 4 , PhD ;   Piergiuseppe Agostoni 5 , MD ;   Andrea Biagi 1 , MD ;   Luca Rossi 1 , MD ;   Andrea Botti 6 , MD ;   Chiara Mari 6 , MD ;   Marco Maccarini 7 , MSc ;   Filippo Pura 7 , MSc ;   Loris Roveda 7 , MSc ;   Alessia Nardecchia 8 , PhD ;   Emanuele Mottola 9 , BA ;   Massimo Nolli 3 , MD ;   Elisabetta Salvioni 5 , MD ;   Massimo Mapelli 5 , MD ;   Marco Agostino Deriu 2 , PhD ;   Dario Piga 7 , PhD ;   Massimo Piepoli 1 , MD, PhD

1 Department of Cardiology , Guglielmo Da Saliceto Hospital , Piacenza , IT

2 PolitoBIOMed Lab , Department of Mechanical and Aerospace Engineering , Politecnico di Torino , Torino , IT

3 Anesthesiology and ICU Department , Guglielmo da Saliceto Hospital , Piacenza , IT

4 TOELT LLC - AI Research and Development , Dubendorf , CH

5 Department of Clinical Sciences and Community Health , Centro Cardiologico Monzino , Istituto di Ricovero e Cura a Carattere Scientifico , Milano , IT

6 Department of Clinical and Experimental Medicine , University of Parma , Parma , IT

7 Dalle Molle Institute for Artificial Intelligence , Università della Svizzera italiana/Scuola universitaria professionale della Svizzera italiana , Lugano , CH

8 Istituto Istruzione Superiore , Casalpusterlengo , IT

9 7HC SRL , Rome , IT

*these authors contributed equally

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