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A study evaluated the use of a fully automated deep learning model for detecting clinically significant prostate cancer on MRI scans. The model was trained using patient-level labels and compared to the predictions of radiologists. Results showed that the DL model was able to accurately identify csPCa without prior information about the location of the tumor, potentially reducing costs and increasing the size of datasets for future studies.
