Shaping the future of cardiac interventions and cardiac surgeries: The impact of virtual reality and artificial intelligence
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Updated: Apr 15, 2026

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Published on: April 5, 2024
Antoine Fakhry AbdelMassih1,2, Abdullah Faris Nasser3, Gawahir AbdelRahman3
1Pediatric Cardiology Unit, Pediatrics' Department, Faculty of Medicine, Cairo University, Cairo, Egypt.
Abstract:
Background: Virtual reality (VR) and artificial intelligence (AI) have had a profound impact on transforming cardiac interventions by enhancing procedure planning, execution, and medical education. Virtual reality enables healthcare professionals to refine their skills by practicing procedures in a simulated environment while also improving patient understanding of their conditions. Artificial intelligence enhances diagnosis and treatment planning by analyzing patient data, detecting patterns, and improving both accuracy and personalized care. The aim of this review was to analyze the anatomical scopes of both technologies in the context of cardiac interventions as well as the radiologic modalities involved in image reconstruction in virtual reality. Methodology: A literature search using the keywords "reviews", "artificial intelligence", "virtual reality", and "cardiac interventions" was conducted across PubMed, Scopus, and Google Scholar. The search was limited to English-language systematic reviews; narrative reviews, individual research articles, editorials, and opinion papers were excluded. Results: An analysis of three reviews encompassing 71 studies revealed the applications of virtual reality (VR) and artificial intelligence (AI) in cardiac surgery. VR training was most frequently applied to mitral valve repair, while VR planning was most common for conotruncal anomalies. AI-driven decision support was most prevalent in heart transplantation. Conclusion: This article highlights the established roles of virtual reality and artificial intelligence in cardiac care, encompassing surgical training, procedural planning, risk assessment, and outcome prediction. However, current VR training methods often rely on time-consuming and expensive imaging techniques like CMR and CT angiography. Within cardiology, AI-driven decision-making is most prominent in heart transplantation.
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