Szczegóły publikacji
Opis bibliograficzny
AI-driven blockchain technology in smart healthcare system: opportunities, challenges and future implications / Yunsheng Zhang, Syed Muhammad Mohsin, Hana Mujlid, Muhammad Sadiq, Syed Muhammad Abrar AKBER, Sheraz Aslam, Junwei Liang // Computer Science Review ; ISSN 1574-0137 . — 2026 — vol. 60 art. no. 100909, s. 1–16. — Bibliogr. s. 13–16, Abstr. — Publikacja dostępna online od: 2026-01-30
Autorzy (7)
- Zhang Yunsheng
- Mohsin Syed Muhammad
- Mujlid Hana
- Sadiq Muhammad
- AGHAbrar Akber Syed Muhammad
- Aslam Sheraz
- Liang Junwei
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 165808 |
|---|---|
| Data dodania do BaDAP | 2026-03-05 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.cosrev.2026.100909 |
| Rok publikacji | 2026 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | Computer Science Review |
Abstract
Blockchain technology in conjunction with artificial intelligence (AI) is transforming smart healthcare systems, by providing enhanced data security, interoperability, and transparency. Integration of AI along with blockchain into smart healthcare systems offers numerous benefits, including supporting decision-making processes, reducing administrative burdens, improving coordination of patient care and automated, trust-based execution of healthcare agreements. This study presents applications of AI-based blockchain technology in the field of smart healthcare and analyzes the state of affairs, highlights the key issues, and identifies perspectives to strengthen the reliability and trustworthiness of future medical systems. The study uses a structured framework to analyze the effectiveness of blockchain in healthcare by contrasting its advantages and disadvantages. Blockchain systems benefit healthcare by improving data security, streamlining data processing, ensuring trust, facilitating telemedicine and remote monitoring, and enabling efficient consent management, automated workflows and medication traceability. In this context, the study introduces a conceptual model namely the trust–automation–interoperability (TAI) synergy framework to guide the design, analysis, and deployment of AI-enabled blockchain solutions for smart healthcare aiming to achieve a sustainable digital health ecosystem by strengthening three fundamental dimensions: trust, automation, and interoperability. However, challenges such as scalability, interoperability, legal ambiguities, security concerns, user experience, acceptance barriers, long-term data storage, connectivity issues, discrepancies between data formats, user identity management, and cost considerations emphasize the importance of strong solutions.
