Title: Editorial for "Performance of Artificial Intelligence‐Aided Diagnosis System for Clinically Significant Prostate Cancer with MRI: A Diagnostic Comparison Study".
Authors: Nather, Julio César; Muglia, Valdair Francisco
Abstract: The primary expectations of using AI-based tools in PCa imaging are to increase the diagnostic accuracy and the reproducibility of prostate MRI. Deep-learning-based artificial intelligence for PI-RADS classification to assist multiparametric prostate MRI interpretation: A development study. Currently, magnetic resonance imaging (MRI) represents one of the best options for the noninvasive assessment of patients with a suspected PCa to attempt to differentiate an indolent lesion from csPCa.
Subjects: PROSTATE cancer; MAGNETIC resonance imaging; DIAGNOSIS
Publication: Journal of Magnetic Resonance Imaging, 2023, Vol 57, Issue 5, p1365
ISSN: 1053-1807
Publication type: Academic Journal
DOI: 10.1002/jmri.28428

Editorial for "Performance of Artificial Intelligence‐Aided Diagnosis System for Clinically Significant Prostate Cancer with MRI: A Diagnostic Comparison Study".

Nather, Julio César; Muglia, Valdair Francisco