A Secure Blockchain–IPFS Framework with AI-Driven Medical Analytics for Decentralized Healthcare Systems

Abstract

Digital infrastructures are becoming very popular in healthcare systems to store and process Electronic Health Records (EHRs), but the majority of current systems are centralized and prone to breach of data, unauthorized access and manipulation of data. The proposed research proposes a solution to these concerns by introducing a smart decentralized healthcare system called MediTrustChain-AI, which combines the blockchain technology, InterPlanetary File System (IPFS), and medical analytics based on artificial intelligence. The medical records are encrypted and stored in IPFS in the proposed architecture with blockchain keeping the content identifiers in the database, access permissions, and audit logs to promote transparency and security. Smart contracts also allow patients to take control of their access rights whereby they can give or withdraw data privileges safely. Another AI-based disease risk prediction system with the ability to analyze medical reports and clinical trends to offer a support to decision making is also deployed in the system. Measurement of storage efficiency, blockchain transaction performance, access control latency, and predictive analytics accuracy was done through experimental evaluation. The findings demonstrate that decentralized storage helped lower the retrieval latency to 1.2-1.7 seconds, whereas smart contract access verification did not exceed 100 milliseconds. AI-based medical prediction module had the highest accuracy of 97.1% and this indicates a diagnostic capability. On the whole, the suggested MediTrustChain-AI model can contribute to a substantial improvement in the healthcare data security, transparency, and smart analytics, which can serve as a stable basis of next-generation decentralized healthcare systems.