Ahmad Musamih

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.