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A DeSci-Driven Blockchain Framework for AI-Augmented Healthcare Research
Garima Singh1,2, Mohd Haroon3, Nudrat Fatima4
1Research Scholar, Department of Computer Science & Engineering, Integral University, Lucknow, India.
Background:
The accelerated digital revolution in healthcare has greatly enhanced data management with electronic health records. Nonetheless, challenging issues of centralized control, privacy breaches, absence of patient ownership of their data, and inability to support decentralized scientific collaboration remain barriers to scalable healthcare research ecosystems. Recent developments in decentralized science (DeSci) create a paradigm shift, using blockchain, cryptographic primitives, and decentralized governance to facilitate transparent, trust-minimized, and collaborative biomedical research. This article provides a DeSci-friendly lightweight blockchain architecture that is used to support privacy-preserving and incentive-sensitive decentralized healthcare research infrastructure.
Methods:
The framework combines a permissioned blockchain with a lightweight hybrid consensus protocol, off-chain storage, and zero-knowledge proof-based authentication to permit secure and privacy-preserving access to data without revealing identity. Also, a tokenomics-based governance layer is proposed to support decentralized engagement, transparent policy implementation, and incentive-based research participation. The suggested system is tested in simulation with the following different network conditions and the key performance metrics such as latency, throughput, and computational cost.
Results:
Experiments prove that the suggested framework offers the following advantages:lower latencygreater throughputenhanced computational efficiencywhen compared to the current blockchain-based healthcare systems such as medical records, Fast Healthcare Interoperability Resources, and HealthChain. In addition, the framework goes past traditional data management by allowing a DeSci-oriented research life cycle, such as decentralized data contribution, validation, and provenance tracking.
Conclusions:
The proposed framework will help build scalable, secure, and patient-centered decentralized healthcare research ecosystems. Furthermore, the framework bridges the gap between blockchain-based healthcare systems and DeSci-driven research ecosystems.
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