Artificial Intelligence in Urology Current Status and Future Perspectives

AI has made a significant progress in multiple facets of surgery over the past decade including diagnostics, outcome prediction, and robotics. However, many obstacles still exist before urology can achieve fully autonomous surgery. Autonomous actions will require a complex network of machine learning, natural language processing, and CV. Each of these facets requires large amounts of data in the form of EHRs, images, and videos that all must be annotated. Thus, the future of urologic surgery must focus on data collection, preparation, and annotation. Other questions must also be answered before AI be-comes widespread in surgery. Autonomous sur-gery must be interpretable to its users and patients, and its ethical concerns regarding racial bias, consideration of treatment implications, and consent must be addressed.

Automated summary

AI has made significant progress in urologic surgery, but there are still obstacles to achieving fully autonomous surgery, such as the challenges in data collection, preparation, and annotation, as well as the need to address ethical concerns and interpretability.