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Artificial Intelligence in Cardiac Surgery and Surgical Training: Opportunities, Risks, and Safeguards for Preserving Expertise

Lookup NU author(s): Professor Djordje JakovljevicORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Abstract

© 2026 by the authors.Artificial intelligence (AI) is entering cardiac surgery through predictive modelling, multimodal imaging, perioperative monitoring, workflow automation, and emerging computer-vision applications. The most mature evidence concerns risk prediction before and after surgery. Even in this domain, however, systematic reviews show that improvements over conventional statistical models are often modest and that routine clinical implementation remains limited. In surgical education, simulation, automated video analysis, and objective performance metrics may expand opportunities for deliberate practice and provide feedback that is less dependent on individual observers. Most of this evidence comes from general, laparoscopic, urological, and robotic surgery rather than cardiac-specific training, and its transferability should not be assumed. The same technologies also create risks. Automation bias, cognitive off-loading, reduced exposure to failure management, and displacement of mentor–trainee interaction may weaken the independent judgement on which safe cardiac surgery depends. Opaque models, dataset shift, inequitable performance, and uncertain accountability add further clinical and ethical concerns. This narrative review examines the current and emerging roles of AI across the cardiac surgical pathway and in cardiothoracic training, while distinguishing demonstrated applications from plausible but unproven uses. We propose a human-in-command framework based on external validation, local performance testing, transparent intended use, preserved manual and crisis-management competencies, simulation of technology failure, faculty oversight, competency-based credentialing, and continuous audit. AI should be judged not by technical novelty alone but by whether it improves care while preserving the ability of surgeons and teams to operate safely when the technology is unavailable or wrong.

Publication metadata

Author(s): Velicki L, Milovancev A, Preveden A, Vuckovic J, Belopavlovic M, Rodic M, Filipovic N, Jakovljevic D

Publication type: Review

Publication status: Published

Journal: Journal of Clinical Medicine

Year: 2026

Volume: 15

Issue: 16

Online publication date: 15/08/2026

Acceptance date: 11/08/2026

ISSN (electronic): 2077-0383

Publisher: Multidisciplinary Digital Publishing Institute (MDPI)

URL: https://doi.org/10.3390/jcm15166313

DOI: 10.3390/jcm15166313

Data Access Statement: No new data were created or analyzed in this study. Data sharing is not applicable to this article. Acknowledgments: During the

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