A systematic review and meta-analysis of artificial intelligence diagnostic accuracy in prostate cancer histology identification and grading.

The accuracy of AI for PCa identification and grading is comparable to expert pathologists. This is a promising approach which has several possible clinical applications resulting in expedite and optimize pathology reports. AI introduction into common practice may be limited by difficult and time-consuming convolutional neural network training and tuning.