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

Joshua S. Jue; David Mikhail; Javier González; Mahmoud Alameddine

doi:10.3390/diagnostics11071213

Diagnostics (Jul 2021)

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

Joshua S. Jue,
David Mikhail,
Javier González,
Mahmoud Alameddine

Affiliations

Joshua S. Jue: Department of Urology, Lenox Hill Hospital, Northwell Health, Zucker School of Medicine at Hofstra/Northwell, New York, NY 10028, USA
David Mikhail: Department of Urology, Lenox Hill Hospital, Northwell Health, Zucker School of Medicine at Hofstra/Northwell, New York, NY 10028, USA
Javier González: Department of Urology, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain
Mahmoud Alameddine: Ottumwa Regional Health Center, Department of Urology, Ottumwa, IA 52501, USA

DOI: https://doi.org/10.3390/diagnostics11071213
Journal volume & issue: Vol. 11, no. 7
p. 1213

Abstract

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Prostate-specific antigen (PSA) has been criticized for its low specificity for prostate cancer, which has led to the increased adoption of additional biomarkers, PSA density (PSAD), and multiparametric magnetic resonance imaging (mpMRI) to increase the localization, risk stratification, and diagnosis of prostate cancer [...]

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Published in Diagnostics

ISSN: 2075-4418 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Medicine: Medicine (General)
Website: http://www.mdpi.com/journal/diagnostics

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