Abstract

The electronic health record (EHR) has been an indispensable tool for healthcare organizations in recent years. However, problems remain associated with EHRs, including fragmented data storage, security vulnerabilities, and limited patient control over personal health information. In this paper, MedLink, a blockchain-powered health record management system, is proposed to provide safe and efficient management of patients’ medical data. The system adopts blockchain architecture to grant access permissions via smart contracts, with encrypted health records being stored externally by using the InterPlanetary File System (IPFS). In addition to security and access permission mechanisms, MedLink incorporates customized machine learning (ML) algorithms to analyze medical data and conduct early diagnosis for diseases such as diabetes, heart conditions, and cancers. Different from the purely general-purpose artificial intelligence generation (AI) model, the proposed method concentrates on creating a customized ML model specifically for particular tasks using existing medical data sources. Experiments have been conducted to evaluate the prototype, revealing promising results regarding data integrity, traceability, and analytical capabilities.

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