A hybrid blockchain migration framework for converting traditional databases into blockchain-based EMR systems Ahmed Al-Busaidi, Joseph Mani, Mohamed Sirajudeen Yoosuf, Vijaya P Scientific Reports, 2026 Electronic Medical Records (EMRs) are crucial to modern healthcare. However, traditional relational databases fail to fulfill increased expectations for integrity, auditability, and compliance in regulated environments. This paper proposes a Hybrid Blockchain Migration Framework that integrates a conventional MySQL-based EMR system (OpenMRS) with a permissioned blockchain network (Hyperledger Fabric). Sensitive data fields are selectively mirrored to the blockchain, ensuring tamper-evident logging while retaining the high performance of SQL for routine operations. A middleware layer, implemented using Java Spring Boot, monitors changes in the EMR and commits cryptographic hashes and metadata to the blockchain in near real-time. We evaluate the hybrid system against both standalone MySQL and full-blockchain implementations using controlled benchmarks, analyzing latency, throughput, resource utilization, and auditability. Results show that the hybrid architecture sustains near-native responsiveness (median 2.1 ms versus 1.6 ms for pure MySQL and 60.5 ms for Fabric) and delivers 480 Transaction Per Second (TPS), while incurring only modest overhead (47% of i7-9750H CPU, 1.15 GB RAM) and enhancing data integrity and compliance with regulations such as Oman’s Personal Data Protection Law (PDPL). The framework is extensible to multi-institutional deployments and supports regulatory alignment, making it a viable pathway for blockchain adoption in clinical settings.
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Human Stress Detection Roshan Fernandes, Anisha P Rodrigues, P. Vijaya, Vijaya Shetty S Cosmic 2024 IEEE International Conference on Computing Semiconductor Mechatronics Intelligent Systems and Communications Proceedings, 2024
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Analysis of leader based clustering algorithms for pattern classification Proceedings of the 2nd Indian International Conference on Artificial Intelligence Iicai 2005, 2005