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A machine learning model based on MRI for the preoperative prediction of bladder cancer invasion depth.

Guihua ChenXuhui FanTao WangEncheng ZhangJialiang ShaoSiteng ChenDongliang ZhangJian ZhangTuanjie GuoZhihao YuanHeting TangYaoyu YuJinyuan ChenXiang Wang
Published in: European radiology (2023)
• Full-sequence MRI prediction model performed better than Vesicle Imaging-Reporting and Data System (VI-RADS) for preoperatively evaluating the invasion status of bladder cancer. • Machine learning methods can extract information from T1-weighted image (T1WI) sequences and benefit bladder cancer invasion prediction.
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