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Abdominal Radiology (New York)|September 22, 2023
Artificial intelligence as diagnostic aiding tool in cases of Prostate Imaging Reporting and Data System category 3: the results of retrospective multi-center cohort studyKexin Wang, Zhangli Xing, Zixuan Kong, et al.Insights Into Imaging|February 10, 2026
Artificial intelligence-derived transition zone PSA density as a triage tool to reduce unnecessary prostate systematic biopsies in MRI-negative menJiaheng Shang, Jingyun Wu, Ruiyi Deng, et al.Insights Into Imaging|January 15, 2025
Evaluating the feasibility of AI-predicted bpMRI image features for predicting prostate cancer aggressiveness: a multi-center studyKexin Wang, Ning Luo, Zhaonan Sun, et al.Insights Into Imaging|April 30, 2023
A multicenter study of artificial intelligence-aided software for detecting visible clinically significant prostate cancer on mpMRIZhaonan Sun, Kexin Wang, Zixuan Kong, et al.Quantitative Imaging in Medicine and Surgery|January 15, 2024
Using an artificial intelligence model to detect and localize visible clinically significant prostate cancer in prostate magnetic resonance imaging: a multicenter external validation studyZhaonan Sun, Kexin Wang, Chenchao Wu, et al.Urologic Oncology|June 1, 2025
Study of AI algorithms on mpMRI and PHI for the diagnosis of clinically significant prostate cancerZeyu Luo, Jialei Li, Kexin Wang, et al.BMC Medicine|November 13, 2024
Comparison of MRI artificial intelligence-guided cognitive fusion-targeted biopsy versus routine cognitive fusion-targeted prostate biopsy in prostate cancer diagnosis: a randomized controlled trialRuiyi Deng, Yi Liu, Kexin Wang, et al.Pageof 2