Enhancing Diagnostic Accuracy and Data Integrity in Healthcare with Blockchain Technology
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
References
More Articles from INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND MATHEMATICAL THEORY
Author: Michael Arnold and Fabio Vitor
Author: Ngozi Samuel Uzougbo, Michael Ominyi, Cyril Chimelie Anichukwueze, Blessing, Chika Jones
Author: Lawal Ahmed Oladimeji, Achori Busayo, Akeju BusayoZainab, Saka Samson, Damilare, Mbah Demian Chidi, Runsewe Similoluwa Mayowa, Oladiti Luqman, Abiodun
Author: Okolo Clement, Eluemuno
Author: Chukumeka Gift Iroanwusi, Davies Isobo Nelson
