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

• मुख्य लेखकों: Halasz, Geza (लेखक), Sperti, Michela (लेखक), Villani, Matteo (लेखक), Michelucci, Umberto (लेखक), Agostoni, Piergiuseppe (लेखक), Biagi, Andrea (लेखक), Rossi, Luca (लेखक), Botti, Andrea (लेखक), Mari, Chiara (लेखक), Maccarini, Marco (लेखक), Pura, Filippo (लेखक), Roveda, Loris (लेखक), Nardecchia, Alessia (लेखक), Mottola, Emanuele (लेखक), Nolli, Massimo (लेखक), Salvioni, Elisabetta (लेखक), Mapelli, Massimo (लेखक), Deriu, Marco Agostino (लेखक), Piga, Dario (लेखक), Piepoli, Massimo (लेखक)
• स्वरूप: पुस्तक
• प्रकाशित: JMIR Publications, 2021-05-01T00:00:00Z.
• विषय: article
• ऑनलाइन पहुंच: Connect to this object online.

BackgroundSeveral 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 stat...