Predicting Prostate Cancer Upgrading of Biopsy Gleason Grade Group at Radical Prostatectomy Using Machine Learning-Assisted Decision-Support Models

Hailang Liu1 Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People’s Republic of China

Kun Tang1 Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People’s Republic of China

Ejun Peng1 Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People’s Republic of China

Liang Wang2 Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People’s Republic of China

Ding Xia1 Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People’s Republic of ChinaCorrespondence[email protected] [email protected]

Zhiqiang Chen1 Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People’s Republic of China

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Cao Xinyu, Jiang Yan, Fang Yin, Wu Peiyan, Song Wenbo, Xing Hanshuo, Wu Xinglong & Xu Guoping. (2023) PFCA-Net: a post-fusion based cross-attention model for predicting PCa Gleason Group using multiparametric MRI. PFCA-Net: a post-fusion based cross-attention model for predicting PCa Gleason Group using multiparametric MRI.

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Shinpei Saito, Shinichi Sakamoto, Kosuke Higuchi, Kodai Sato, Xue Zhao, Ken Wakai, Manato Kanesaka, Shuhei Kamada, Nobuyoshi Takeuchi, Tomokazu Sazuka, Yusuke Imamura, Naohiko Anzai, Tomohiko Ichikawa & Eiryo Kawakami. (2023) Machine-learning predicts time-series prognosis factors in metastatic prostate cancer patients treated with androgen deprivation therapy. Scientific Reports 13:1.
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Moumen T. El-Melegy, Ahmed Mamdouh, Samia A. Ali & Ayman S. El-Baz. (2022) Prostate Cancer Diagnosis from Structured Clinical Biomarkers with Deep Learning. Prostate Cancer Diagnosis from Structured Clinical Biomarkers with Deep Learning.

Ahmed Mamdouh, Moumen T. El-Melegy, Samia A. Ali & Ayman S. El-Baz. (2022) Prediction of The Gleason Group of Prostate Cancer from Clinical Biomarkers: Machine and Deep Learning from Tabular Data. Prediction of The Gleason Group of Prostate Cancer from Clinical Biomarkers: Machine and Deep Learning from Tabular Data.

Mpho Mokoatle, Darlington Mapiye, Vukosi Marivate, Vanessa M. Hayes & Riana Bornman. (2022) Discriminatory Gleason grade group signatures of prostate cancer: An application of machine learning methods. PLOS ONE 17:6, pages e0267714.
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Junlong Zhuang, Yansheng Kan, Yuwen Wang, Alessandro Marquis, Xuefeng Qiu, Marco Oderda, Haifeng Huang, Marco Gatti, Fan Zhang, Paolo Gontero, Linfeng Xu, Giorgio Calleris, Yao Fu, Bing Zhang, Giancarlo Marra & Hongqian Guo. (2022) Machine Learning-Based Prediction of Pathological Upgrade From Combined Transperineal Systematic and MRI-Targeted Prostate Biopsy to Final Pathology: A Multicenter Retrospective Study. Frontiers in Oncology 12.
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Predicting Prostate Cancer Upgrading of Biopsy Gleason Grade Group at Radical Prostatectomy Using Machine Learning-Assisted Decision-Support Models

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Predicting Prostate Cancer Upgrading of Biopsy Gleason Grade Group at Radical Prostatectomy Using Machine Learning-Assisted Decision-Support Models

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