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The New England Journal of Medicine|March 5, 2020
MRI-Targeted, Systematic, and Combined Biopsy for Prostate Cancer DiagnosisMichael Ahdoot, Andrew R Wilbur, Sarah E Reese, et al.BJU International|May 30, 2019
Use of multiparametric magnetic resonance imaging and fusion-guided biopsies to properly select and follow African-American men on active surveillanceJonathan B Bloom, Amir H Lebastchi, Samuel A Gold, et al.The Journal of Urology|July 28, 2020
PI-RADS® Category as a Predictor of Progression to Unfavorable Risk Prostate Cancer in Men on Active SurveillanceAlex Z Wang, Luke P O’Conno, Nitin K Yerram, et al.The American Journal of Pathology|October 29, 2022
Deep Domain Adversarial Learning for Species-Agnostic Classification of Histologic Subtypes of OsteosarcomaSushant Patkar, Jessica Beck, Stephanie Harmon, et al.Clinical Imaging|May 27, 2008
Peritoneal carcinomatosis in urinary bladder cancerBaris Turkbey, Ceyla Basaran, Musturay Karcaaltincaba, et al.Diagnostics (Basel, Switzerland)|March 13, 2025
Comparing and Combining Artificial Intelligence and Spectral/Statistical Approaches for Elevating Prostate Cancer Assessment in a Biparametric MRI: A Pilot StudyRulon Mayer, Yuan Yuan, Jayaram Udupa, et al.European Urology Focus|September 18, 2017
Using Imaging to Predict Treatment Response in Genitourinary MalignanciesAmir H Lebastchi, Matthew J Watson, Christopher M Russell, et al.Abdominal Radiology (New York)|May 4, 2016
A urologist's perspective on prostate cancer imaging: past, present, and futureArvin K George, Baris Turkbey, Subin G Valayil, et al.The Review of Scientific Instruments|November 10, 2009
A method for correlating in vivo prostate magnetic resonance imaging and histopathology using individualized magnetic resonance-based moldsVijay Shah, Thomas Pohida, Baris Turkbey, et al.Frontiers in Artificial Intelligence|August 6, 2021
AI-Assisted CT as a Clinical and Research Tool for COVID-19Zion Tsz Ho Tse, Sierra Hovet, Hongliang Ren, et al.Pageof 60