磁共振成像（MRI）对改进识别高级别前列腺癌的深度学习模型的价值。对金泰尔等人的评论。通过在深度学习模型中结合不同的前列腺特异性抗原（PSA）分子形式和PSA密度优化识别高级别前列腺癌。2021年，，335。
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. 2021, , 335.
作者信息
Jue Joshua S, Mikhail David, González Javier, Alameddine Mahmoud
机构信息
Department of Urology, Lenox Hill Hospital, Northwell Health, Zucker School of Medicine at Hofstra/Northwell, New York, NY 10028, USA.
Department of Urology, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain.
出版信息
Diagnostics (Basel). 2021 Jul 5;11(7):1213. doi: 10.3390/diagnostics11071213.
Abstract
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 [...].
摘要
前列腺特异性抗原（PSA）因其对前列腺癌的低特异性而受到批评，这导致更多地采用其他生物标志物、前列腺特异抗原密度（PSAD）和多参数磁共振成像（mpMRI）来提高前列腺癌的定位、风险分层和诊断水平[...]。
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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. 2021, , 335.磁共振成像（MRI）对改进识别高级别前列腺癌的深度学习模型的价值。对金泰尔等人的评论。通过在深度学习模型中结合不同的前列腺特异性抗原（PSA）分子形式和PSA密度优化识别高级别前列腺癌。2021年，，335。
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