Artificial intelligence in early diagnosis of prostate cancer.

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.