A review of current advancements and limitations of artificial intelligence in genitourinary cancers.

摘要: Advances in deep learning and neural networking have allowed clinicians to understand the impact that artificial intelligence (AI) could on improving clinical outcomes resources expenditures. In realm of genitourinary (GU) cancers, AI has had particular success diagnosis treatment prostate, renal, bladder cancers. Numerous studies developed methods utilize networks automate prognosis prediction, plan optimization, patient education. Furthermore, many groups explored other techniques, including digital pathology expert 3D modeling systems. Compared established methods, nearly all showed some level improvement there is evidence pipelines can reduce subjectivity management GU malignancies. However, despite potential benefits utilizing urologic oncology, are notable limitations when combating real-world data sets. Thus, it vital more prospective be conducted will allow for a better understanding both cancer patients urologists.