Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Shaping the future of cardiac interventions and cardiac surgeries: The impact of virtual reality and artificial intelligence
0
Zitationen
7
Autoren
2025
Jahr
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.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.393 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.259 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.688 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.502 Zit.