RESUMO
Global Cancer Statistics for 2020 show that urinary system tumors account for approximately 13% of the total number of cancers. At present, the diagnostic methods of urinary system tumors are imaging, endoscopy, and pathological examination. As the gold standard of tumor diagnosis, pathological examination has problems such as lack of pathologists and long operation time. Artificial intelligence (AI), with a strong ability for pathology image recognition and feature analysis, can be used as an auxiliary diagnosis. It has realized automatic diagnosis, typing, staging, grading, and prognosis prediction in several urinary system tumors. However, AI still has many shortcomings, which limit its clinical application. This article will review the progress of AI and its application in the pathological study of urinary system tumors.