Mortality Prediction of COVID-19 Patients Using Radiomic and Neural Network Features Extracted from a Wide Chest X-ray Sample Size: A Robust Approach for Different Medical Imbalanced Scenarios

Aim: The aim of this study was to develop robust prognostic models for mortality prediction of COVID-19 patients, applicable to different sets of real scenarios, using radiomic and neural network features extracted from chest X-rays (CXRs) with a certified and commercially available software. Method...

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Main Authors: Mauro Iori, Carlo Di Castelnuovo, Laura Verzellesi, Greta Meglioli, Davide Giosuè Lippolis, Andrea Nitrosi, Filippo Monelli, Giulia Besutti, Valeria Trojani, Marco Bertolini, Andrea Botti, Gastone Castellani, Daniel Remondini, Roberto Sghedoni, Stefania Croci, Carlo Salvarani
פורמט: Artigo
שפה:Inglês
יצא לאור: MDPI AG 2022-04-01
סדרה:Applied Sciences
נושאים:
machine learning
radiomics
COVID-19
X-ray radiography
under-sampling
גישה מקוונת:https://www.mdpi.com/2076-3417/12/8/3903
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