Potential of artificial intelligence in cardiac surgery: a systematic review

The introduction of artificial intelligence (AI) technologies pushes the boundaries in cardiac surgery, but safe clinical practice requires systematization of data on its capabilities and limitations. The study aim is to systematize current data on the use of AI in cardiac surgery and identify promising areas for its clinical implementation. This systematic review of data from PubMed, Scopus, the Cochrane Library, Google Scholar, and Web of Science for the period 2000-2025 in accordance with the PRISMA criteria analyzed studies on AI use at all stages of cardiac surgery. Based on the analysis of 179 studies, machine learning models demonstrate higher sensitivity compared to traditional diagnostic methods and risk scores in predicting postoperative outcomes and complications. AI-based robotic systems and computer vision can improve the precision of surgical interventions, and the use of AI for postoperative monitoring can improve patient outcomes and rehabilitation. The main barriers to scaling these technologies remain data insufficiency, ethical considerations, and the difficulty of integrating them into clinical practice. Thus, AI has the potential to improve the quality of cardiac surgical care. However, realizing this potential requires validating algorithms, eliminating systemic errors, and developing transparent ethical and legal standards.