IIARD International Institute of Academic Research and Development

INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND MATHEMATICAL THEORY (IJCSMT )

E-ISSN 2545-5699
P-ISSN 2695-1924
VOL. 11 NO. 4 2025
DOI: 10.56201/ijcsmt.vol.11.no4.2025.pg.46.65

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Enhancing Diagnostic Accuracy and Data Integrity in Healthcare with Blockchain Technology

Ike Mgbeafulike, Nwosa Destiny

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Abstract

The integration of Artificial Intelligence (AI) and blockchain technologies offers transformative potential in addressing critical challenges within healthcare systems, including diagnostic inaccuracies, data breaches, and lack of transparency. This study presents the design, implementation, and evaluation of an intelligent medical diagnostic system that combines AI-driven decision support with blockchain-enabled data management. The system architecture incorporates key components such as a patient interface for data collection, an AI diagnostic engine utilizing neural networks and fuzzy logic, a decision support system (DSS), and a blockchain layer for secure data logging and consent management. Implementation was carried out using Python (TensorFlow, Scikit-learn) for AI models, Flask for system integration, and Ethereum for blockchain functionality. Evaluation metrics such as diagnostic accuracy, system efficiency, and user feedback were employed to validate performance. Results indicate a diagnostic accuracy of 95%, blockchain transaction latency under 3 seconds, and high user satisfaction regarding usability and data control. Despite challenges in scalability, regulatory compliance, and legacy system integration, the system demonstrates significant promise in enhancing clinical decision-making, safeguarding patient data, and supporting compliance with healthcare regulations. This research contributes a scalable, secure, and intelligent platform for proactive and patient-centric healthcare delivery.

keywords:

Medical diagnosis; Artificial Intelligence (AI); Blockchain; Neural Networks; Decision Support System (DSS); Electronic Health Records (EHR); Healthcare data security.

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