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

Andrey O MorozovMark TaratkinAndrey BazarkinGómez Rivas Juan Stefano Puliatti Enrico Checcucci Ines Rivero BelenchonKarl-Friedrich KowalewskiAnastasia ShpikinaNirmish SinglaJeremy Yuen Chun TeohVasiliy KozlovSeverin RodlerPietro PiazzaHarun FajkovicMaxim YakimovAndre Luis Abreu Giovanni Enrico Cacciamani Dmitry V Enikeevnull null

Published in: Prostate cancer and prostatic diseases (2023)

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.

Keyphrases

artificial intelligence
deep learning
convolutional neural network
prostate cancer
machine learning
big data
healthcare
bioinformatics analysis
primary care
radical prostatectomy
quality improvement
virtual reality