Technology & Management Review

Peer Reviewed Article

Vol. 5 (2020)

Blockchain-Driven AI Solutions for Medical Imaging and Diagnosis in Healthcare

Submitted
2025 January 1
Published
2020-04-25

Abstract

This research examines how blockchain and AI might improve medical imaging and diagnosis. Blockchain is reviewed to improve diagnosis accuracy and efficiency in AI-driven medical imaging by addressing data security, privacy, and transparency. The research synthesizes current accomplishments and identifies gaps in technology integration using secondary data from peer-reviewed journals, conference proceedings, and reports. Significant discoveries demonstrate blockchain's ability to secure and decentralize data exchange and enable collaborative AI model building while protecting patient privacy. Blockchain increases AI model openness and traceability, boosting healthcare decision-making trust and accountability. Diagnostic processes are streamlined by AI and blockchain, boosting operational efficiency and patient outcomes. Scalability, interoperability, and regulatory compliance remain issues. The research stresses the necessity for clear regulatory frameworks and ethical principles to overcome these constraints. Policy implications include standardizing interoperability standards, investing in scalable blockchain technologies, and creating ethical frameworks for responsible AI usage in healthcare. Blockchain-driven AI technologies may improve medical imaging and diagnostics, creating a more secure, efficient, patient-centered healthcare environment.

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