Application of artificial intelligence in urology: the healthcare structure of the future

Popov S.V., Guseinov R.G., Sivak K.V., Bunenkov N.S., Perepelitsa V.V. , Sengirbaev D.I., Lelyavina T.A.

1) St. Luke Clinical Hospital, St. Petersburg, Russia; 2) S.M. Kirov Military Medical Academy, Ministry of Defense of the Russian Federation, St. Petersburg, Russia; 3) A.A. Smorodintsev Research Institute of Influenza, Ministry of Health of Russia, St. Petersburg, Russia; 4) S.D. Asfendiyarov Kazakh National Medical University, Ministry of Health of the Republic of Kazakhstan, Almaty, Kazakhstan; 5) V.A. Almazov National Medical Research Centre, Ministry of Health of Russia, St. Petersburg, Russia

Introduction. Artificial intelligence (AI) is one of the most innovative and promising fields of modern technology, exerting a significant impact on various areas of medicine, including urology. AI is increasingly being used not only for the diagnosis of urological conditions, but also for their treatment and prognostic assessment. The literature search was performed in the electronic databases PubMed, Web of Science, Scopus, CyberLeninka, and eLibrary. The inclusion criteria were original studies on the application of AI methods in urology and literature reviews on the topic. The exclusion criteria were preliminary studies and conference abstracts. The broad potential of AI methods in various fields of urology has been demonstrated. Machine learning and deep learning algorithms show high accuracy in diagnosing urological diseases based on laboratory and imaging data. AI models can assist surgeons in operative planning and intraoperative navigation. AI has also shown potential in predicting recurrences and complications based on the analysis of clinical data. Successful examples of AI implementation have been reported in urooncology, nephrology, and andrology. Future directions for improving AI models and integrating them into clinical practice are discussed.
Conclusion. Artificial intelligence demonstrates high efficacy across various fields of urology from image analysis to surgical navigation. However, its implementation requires addressing issues of ethics and system validation. With the proper approach, the integration of AI and physicians’ expertise can significantly improve disease diagnosis and patient treatment. Further research in this area is promising and may lead to breakthroughs in urological practice.

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About the Authors

Corresponding author: T.A. Lelyavina – Ph.D., MD, Professor, Department of Pathophysiology, Institute of Medical Education, V.A. Almazov National Medical Research Centre, Ministry of Health of Russia; Researcher, St. Luke Clinical Hospital, St. Petersburg, Russia; e-mail: tatianalelyavina@mail.ru

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