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Bayesian Networks in the Management of Hospital Admissions: A Comparison between Explainable AI and Black Box AI during the Pandemic.
Nicora, Giovanna; Catalano, Michele; Bortolotto, Chandra; Achilli, Marina Francesca; Messana, Gaia; Lo Tito, Antonio; Consonni, Alessio; Cutti, Sara; Comotto, Federico; Stella, Giulia Maria; Corsico, Angelo; Perlini, Stefano; Bellazzi, Riccardo; Bruno, Raffaele; Preda, Lorenzo.
Afiliación
  • Nicora G; Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy.
  • Catalano M; Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy.
  • Bortolotto C; Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy.
  • Achilli MF; Radiology Institute, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy.
  • Messana G; Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy.
  • Lo Tito A; Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy.
  • Consonni A; Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy.
  • Cutti S; Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy.
  • Comotto F; Medical Direction, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy.
  • Stella GM; Reply S.p.A. Corso Francia, 110, 10143 Turin, Italy.
  • Corsico A; Department of Internal Medicine and Therapeutics, University of Pavia, 27100 Pavia, Italy.
  • Perlini S; Unit of Respiratory Diseases, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy.
  • Bellazzi R; Department of Internal Medicine and Therapeutics, University of Pavia, 27100 Pavia, Italy.
  • Bruno R; Unit of Respiratory Diseases, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy.
  • Preda L; Department of Internal Medicine and Therapeutics, University of Pavia, 27100 Pavia, Italy.
J Imaging ; 10(5)2024 May 10.
Article en En | MEDLINE | ID: mdl-38786571
ABSTRACT
Artificial Intelligence (AI) and Machine Learning (ML) approaches that could learn from large data sources have been identified as useful tools to support clinicians in their decisional process; AI and ML implementations have had a rapid acceleration during the recent COVID-19 pandemic. However, many ML classifiers are "black box" to the final user, since their underlying reasoning process is often obscure. Additionally, the performance of such models suffers from poor generalization ability in the presence of dataset shifts. Here, we present a comparison between an explainable-by-design ("white box") model (Bayesian Network (BN)) versus a black box model (Random Forest), both studied with the aim of supporting clinicians of Policlinico San Matteo University Hospital in Pavia (Italy) during the triage of COVID-19 patients. Our aim is to evaluate whether the BN predictive performances are comparable with those of a widely used but less explainable ML model such as Random Forest and to test the generalization ability of the ML models across different waves of the pandemic.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Imaging Año: 2024 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Imaging Año: 2024 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Suiza