Abstract
This review aims to shed light on recent applications of artificial intelligence in urologic oncology. Artificial intelligence algorithms harness the wealth of patient data to assist in diagnosing, staging, treating, and monitoring genitourinary malignancies. Successful applications of artificial intelligence in urologic oncology include interpreting diagnostic imaging, pathology, and genomic annotations. Many of these algorithms, however, lack external validity and can only provide predictions based on one type of dataset. Future applications of artificial intelligence will need to incorporate several forms of data in order to truly make headway in urologic oncology. Researchers must actively ensure future artificial intelligence developments encompass the entire prospective patient population.
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