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Protecting Personal Healthcare Record Using Blockchain & Federated Learning Technologies

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dc.date.accessioned2023-06-19T02:22:36Z-
dc.date.available2023-06-19T02:22:36Z-
dc.date.issued2022-03-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/194837-
dc.description.abstractFor decades artificial intelligence (AI) has been used for various applications in the healthcare industry. Machine learning and artificial intelligence algorithms allow us to diagnose and customize medical care and follow-up plans to get better results, and during the covid19 pandemic, it was found that AI models have been using to predict the Covid-19 symptoms, understanding how it spreads, speeding up research and treatment using medical data. However, it is very challenging to make a robust AI model and use it in a real-time and real-world environment since most organizations do not want to share their data with other third parties due to privacy concerns, furthermore, it is difficult to build a generalized prediction model because of the fragmented nature of the patient data across the healthcare system. To solve the above problems, this paper presents a solution based on blockchain and AI technologies. The blockchain will securely protect the data access and AI-based federated learning for building a robust model for global and realtime usage.-
dc.description.statementOfResponsibilityrestriction-
dc.relation.isPartOfInternational Conference on Advanced Communication Technology-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleProtecting Personal Healthcare Record Using Blockchain & Federated Learning Technologies-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentOther-
dc.contributor.googleauthorSatyabrata Aich-
dc.contributor.googleauthorNday Kabulo Sinai-
dc.contributor.googleauthorSaurabh Kumar-
dc.contributor.googleauthorMohammed Ali-
dc.contributor.googleauthorYu Ran Choi-
dc.contributor.googleauthorMoon-IL Joo-
dc.contributor.googleauthorHee-Cheol Kim-
dc.identifier.doi10.23919/ICACT51234.2021.9370566-
dc.identifier.urlhttps://ieeexplore.ieee.org/document/9370566-
dc.citation.startPage20533113-
dc.identifier.bibliographicCitationInternational Conference on Advanced Communication Technology, : 20533113, 2022-03-
Appears in Collections:
1. College of Medicine (의과대학) > Others (기타) > 1. Journal Papers

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