Reply to Jue et al. Value of MRI to Improve Deep Learning Model That Identifies High-Grade Prostate Cancer. Comment on “Gentile et al. Optimized Identification of High-Grade Prostate Cancer by Combining Different PSA Molecular Forms and PSA Density in a Deep Learning Model. Diagnostics 2021, 11, 335”

Affiliations

Francesco Gentile: Department of Experimental and Clinical Medicine, University Magna Graecia of Catanzaro, 88100 Catanzaro, Italy
Matteo Ferro: Division of Urology, European Institute of Oncology (IEO), IRCCS, Via Ripamonti 435, 20141 Milan, Italy
Bartolomeo Della Ventura: Department of Physics “Ettore Pancini”, University of Naples “Federico II”, Via Cintia 26 Ed. G, 80126 Naples, Italy
Evelina La Civita: Department of Translational Medical Sciences, University of Naples “Federico II”, 80131 Naples, Italy
Antonietta Liotti: Department of Translational Medical Sciences, University of Naples “Federico II”, 80131 Naples, Italy
Michele Cennamo: Department of Translational Medical Sciences, University of Naples “Federico II”, 80131 Naples, Italy
Dario Bruzzese: Department of Public Health, University of Naples “Federico II”, 80131 Naples, Italy
Raffaele Velotta: Department of Physics “Ettore Pancini”, University of Naples “Federico II”, Via Cintia 26 Ed. G, 80126 Naples, Italy
Daniela Terracciano: Department of Translational Medical Sciences, University of Naples “Federico II”, 80131 Naples, Italy

Abstract

In their comment “Value of MRI to Improve Deep Learning Model That Identifies High-Grade Prostate Cancer [...]