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Confluence of Blockchain and Artificial Intelligence Technologies for Secure and Scalable Healthcare Solutions: A Review

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dc.contributor.author Chamola, Vinay
dc.date.accessioned 2023-03-20T04:15:08Z
dc.date.available 2023-03-20T04:15:08Z
dc.date.issued 2022-12
dc.identifier.uri https://ieeexplore.ieee.org/abstract/document/10002899
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9842
dc.description.abstract Blockchain (BC) and Artificial Intelligence (AI) technologies have independent applications in multiple industries, including banking, finance, health care, construction, transportation, hospitality, manufacturing, and insurance, to name a few. Moreover, these two technologies can be integrated seamlessly, thanks to their complementary and mutually-supportive features. AI algorithms can make the medical blockchain storage efficient by their processing algorithms, also playing the role of knowledgeable gatekeepers. Blockchain can support AI models by providing secure, sizeable, traceable, diverse, and immutable healthcare data for the training purpose. The integration of BC and AI has multiple use cases in the healthcare industry ranging from disease prediction to pandemic management. Previously, researchers have reviewed the applications of each of these technologies in health care independently. Although the integration of BC and AI has been fruitful, to the best of our knowledge, there has been no work in the past reviewing the confluence of these two technologies in the health care sector. We have classified the works based on two different classification schemes: application-based and AI-training paradigm-based classification. We have also provided a compilation of tools used in the integrated systems of BC and AI for healthcare. We identified that the integration of BC and AI technologies had been applied in quite different areas of healthcare ranging from biomedical research to pandemic management. It is also noted that the supervised learning algorithms and federated learning paradigm for secure decentralized AI model training are often used in the integration. Our findings reveal that majority of the reviewed works use blockchain as a secure database for AI models. Further, we also have pointed out the potential applications of these two technologies in health care. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject EEE en_US
dc.subject Artificial intelligence (AI) en_US
dc.subject Medical services en_US
dc.subject Blockchains en_US
dc.subject Data models en_US
dc.subject Biological system modeling en_US
dc.subject Medical diagnostic imaging en_US
dc.title Confluence of Blockchain and Artificial Intelligence Technologies for Secure and Scalable Healthcare Solutions: A Review en_US
dc.type Article en_US


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