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Artificial intelligence in early diagnosis of prostate cancer DOI: 10.29188/2222-8543-2025-18-1-42-49
- Vasilyev A.O. – PhD, Assistant of the Department of Urology of the «Russian University of Medicine» of the Ministry of Health of Russia on the basis of the State Budgetary Healthcare Institution MMNC named after S.P. Botkin of the Moscow Department of Health; Moscow, Russia; RSCI Author ID 832619, https://orcid.org/0000-0001-5468-0011
- Govorov A.V. – Dr. Sci., Professor of the Russian Academy of Sciences, Professor of the Department of Urology of the «Russian University of Medicine» of the Ministry of Health of Russia on the basis of the State Budgetary Healthcare Institution MMNC named after S.P. Botkin Moscow Department of Health; Moscow, Russia; RSCI Author ID 711844, https://orcid.org/0000-0003-3299-0574
- Kim Yu.A. – PhD, urologist of the State Budgetary Healthcare Institution MMNC named after S.P. Botkin Moscow Department of Health; Moscow, Russia; RSCI Author ID 1068822, https://orcid.org/0000-0001-6390-3408
- Arutyunyan P.A. – leading specialist of the Urology Department of the «Research Institute of Oc- cupational Health and Medical Care of the Moscow Health Department», urologist, postgradu- ate student of the Urology Department of the «Russian University of Medicine» of the Ministry of Health of Russia on the basis of the State Budgetary Healthcare Institution MMNC named after S.P. Botkin of the Moscow Health Department; Moscow, Russia; RSCI Author ID 1193661,https://orcid.org/0000-0002-6228-012X
- Pushkar D.Yu. – Dr. Sci., academician of the Russian Academy of Sciences, Professor, Head of the Urology Department of the «Russian University of Medicine» of the Ministry of Health of Russia on the basis of the State Budgetary Healthcare Institution MMNC named after S.P. Botkina Moscow Department of Health, Chief Urologist of the Ministry of Health of Russia, Chief Urologist of the Moscow Department of Health, Head of the Moscow Urology Center; Moscow, Russia; RSCI Author ID 417122, https://orcid.org/0000-0002-6096-5723
553 Introduction. To assess the prospects of using artificial intelligence (AI) for the diagnosis and treatment of prostate cancer (PCa) and to evaluate the impact of AI on treatment efficacy.
Materials and Methods. A systematic literature review was conducted using scientific databases based on key queries related to AI and PCa. Studies from the last 10 years were included.
Results. AI algorithms, such as machine learning (ML) and deep learning (DL), improve the quality of PCa diagnostics, minimize subjective factors, and optimize the diagnostic process. The implementation of computer-aided detection (CAD) systems also enhances diagnostic accuracy, while the results depend on the expertise of specialists.
Discussion. AI-based systems have the potential to improve diagnostics, personalize treatment, and reduce healthcare costs. However, issues related to the quality of AI training data and the interpretation of algorithms require further investigation.
Conclusions. The use of AI in PCa diagnostics is a promising direction. However, additional research is needed for a comprehensive assessment of effective systems and the implementation process.
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