Machine and Deep Learning Algorithms for COVID-19 Mortality …

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2023
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  • DOI 10.3390/electronics12183878
  • OpenAlex ID W4386743165
  • Type Article
  • Language EN
  • Published 14 Sep 2023
  • Volume 12 (18)
  • Pages 3878
  • Source Electronics
  • Publisher Multidisciplinary Digital Publishin…
  • FWCI 0.50
  • Countries 1
  • Institutions 7
  • Added 15 Sep 2023
  • Updated 16 Oct 2026
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Machine and Deep Learning Algorithms for COVID-19 Mortality Prediction Using Clinical and Radiomic Features

Article 2023 EN Gold

Aim: Machine learning (ML) and deep learning (DL) predictive models have been employed widely in clinical settings. Their potential support and aid to the clinician of providing an objective measure that can be shared among different centers enables the possibility of building more robust multicentric studies. This study aimed to propose a user-friendly and low-cost tool for COVID-19 mortality pre…

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UN Sustainable Development Goals
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15 authors
#AuthorInstitutionsORCID
1 Laura Verzellesi Azienda Sanitaria Unità Locale… (IT)
2 Andrea Botti Azienda Sanitaria Unità Locale… (IT)
3 Marco Bertolini Azienda Sanitaria Unità Locale… (IT)
4 Valeria Trojani Corresponding Azienda Sanitaria Unità Locale… (IT)
5 Gianluca Carlini University of Bologna (IT)
6 Andrea Nitrosi Azienda Sanitaria Unità Locale… (IT)
7 Filippo Monelli Azienda Sanitaria Unità Locale… (IT)
8 Giulia Besutti University of Modena and Reggi… (IT) Azienda Sanitaria Unità Locale… (IT)
9 Gastone Castellani IRCCS Azienda Ospedliero-Unive… (IT)
10 Daniel Remondini Istituto Nazionale di Fisica N… (IT) University of Bologna (IT)
11 Gianluca Milanese University of Parma (IT) Ospedale di Parma (IT)
12 Stefania Croci Azienda Sanitaria Unità Locale… (IT)
13 Nicola Sverzellati University of Parma (IT) Ospedale di Parma (IT)
14 Carlo Salvarani University of Modena and Reggi… (IT) Azienda Sanitaria Unità Locale… (IT)
15 Mauro Iori Corresponding Azienda Sanitaria Unità Locale… (IT)
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