Reimagining cardiac care with AI, LLMs, blockchain, and metaverse

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Authors: Ahmad Musamih, Khaled Salah, Mohammed Mispah Said Omar, Samer Ellaham
Cited by: 1

Abstract

Objective: Artificial intelligence (AI) is reshaping cardiology by analyzing complex data and enabling precision care. Among its recent advances, large language models (LLMs) have gained prominence for their potential to enhance clinical reasoning, documentation, and education. Alongside AI, blockchain, and metaverse-based extended reality (XR) are transforming data security, interoperability, and immersive visualization. This review consolidates the current literature on these technologies, evaluates their roles in cardiology, and introduces a conceptual framework for integrating them to support a secure, intelligent, and interactive digital ecosystem. Methods: A structured narrative review was conducted using PubMed and Scopus to identify peer-reviewed studies published between 2018 and 2025. Systematic identification and screening of the literature were performed and reported using PRISMA 2020. Eligible publications included original research, reviews, and conceptual papers addressing the use of AI, LLMs, blockchain, or XR in cardiology. The literature was analyzed thematically, and findings were synthesized qualitatively to describe applications, limitations, and opportunities for integration. Results: Across 50 studies, LLMs showed promise in documentation, education, and decision support but faced challenges in accuracy, validation, and bias. Blockchain applications improved data exchange, consent management, and provenance tracking, though scalability and interoperability remain unresolved. XR technologies enhanced procedural precision, training, and patient engagement but were limited by cost and validation. A conceptual integration model illustrates how these technologies function within a unified cardiovascular ecosystem where blockchain provides the trust layer, LLMs deliver analytical intelligence, and XR enables immersive interaction. Conclusion: Integrating AI, LLMs, blockchain, and XR offers a pathway toward intelligent, secure, and interactive cardiovascular care. Future research should validate integrated frameworks, develop ethical and regulatory standards, and promote responsible adoption of AI in cardiology.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Explainable Artificial Intelligence (XAI) Machine Learning in Healthcare

Publication details

Journal / source
Global Cardiology Science and Practice
Publisher
Global Cardiology Science and Practice
Volume
2026
Issue
1
Pages
e202609–e202609
Publication date
27 February 2026
Language
EN