Issue |
ITM Web Conf.
Volume 73, 2025
International Workshop on Advanced Applications of Deep Learning in Image Processing (IWADI 2024)
|
|
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Article Number | 03007 | |
Number of page(s) | 7 | |
Section | Blockchain, AI, and Technology Integration | |
DOI | https://doi.org/10.1051/itmconf/20257303007 | |
Published online | 17 February 2025 |
Integration of Blockchain and Artificial Intelligence in Healthcare: Enhancing Data Security and Operational Efficiency
Ulster College, Shaanxi University of Science & Technology, 710021 Xi’an, China
* Corresponding author: 202315030403@sust.edu.cn
Whereas the demands for data privacy and security in healthcare have been tending to an ever-higher level, integration between blockchain and Artificial Intelligence (AI) technology has thereafter become a new innovative method that could solve these problems. Since many studies related to the application of blockchain in the field of data security and artificial intelligence in medical diagnosis have been proposed, research on the integration of this new technology in the medical field is still required. The paper focused essentially on the amalgamation of these two technologies, elaborating on novel practices in clinical diagnosis, medical records, and pharmaceutical supply chain management. This paper conducted a literature review and case analysis to examine how blockchain ensures data immutability with decentralized storage mechanisms and how AI utilizes this data through deep learning and real-time analysis for its decision-making system. The examination results indicate that blockchain decentralizes data for storing patients' privacy and integrity, while AI can enhance the accuracy of diagnosis and decision-making for treatment. Moreover, information transparency and operational efficiency will be further developed by integrating the two technologies. Based on the conclusion of this study, blockchain and AI integrated technology holds great potential to enable the healthcare industry toward intelligent and personalized development. Despite the technical standardization barrier and protection of privacy, future research should focus on optimizing scalability to further advance the integration of these two technologies in healthcare services.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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