A systematic review of current advancements of artificial intelligence in genitourinary cancers

Abstract

Recently, advances in machine learning and neural network technology have allowed artificial intelligence (AI) to further promote guidance of clinical diagnosis, treatment and resource expenditures. In genitourinary cancers, AI has made huge progress in improving the diagnosis and treatment of prostate, kidney and bladder cancers. Numerous studies have developed methods to utilize neural networks to automate prognostic prediction, treatment plan optimization and patient follow-up education. Obviously, AI guidance could markedly reduce the subjectivity of diagnosis and treatment management of genitourinary cancers. However, although the application of AI in cancer treatment has become a research hotspot in modern technology, there still exist obvious limitations of AI management when compared with real-world clinical strategies. Therefore, this article summarized the current advantages and disadvantages of AI to provide novel insights for the future application of AI in the precision, personalized diagnosis and treatment, and long-term management of both patients and urologists.

Keywords

• |artificial intelligence|machine learning|genitourinary cancers|prostate cancer|renal cancer|bladder cancer