International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Volume 7 Issue 6
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Blockchain-Integrated Federated Learning for Secure Patient-Centric Care in Healthcare 5.0

Author(s) Dr. Rahul Srova, Dr. Trinjana Sachdeva, Dr. Archana Shahi
Country India
Abstract Healthcare 5.0 shows an evolution in intelligent, integrated, and patient-centric health systems, which is based on the interconnected use of technologies such as Internet of Medical Things (IoMT), Artificial Intelligence (AI) and edge computing. But, with increasing dependence on these technologies, it also causes several concers, such as data privacy, security, and interoperability. The sharing of data at one centre for training can increase the risk of data breach, raising worries about data safety. Federated learning, on the other hand, allows training of machine learning models without sharing data in a decentralised manner. The patient privacy and data remain protected as sensitive data can remain on the device. Simultaneously, Blockchain improves this framework by providing a secure and transparent record of data transactions, providing accurate data tracking which further reduces the risk of data tampering. In this paper, we will evaluate the integration of Federated learning with blockchain technology in the framework of Internet of Medical Things (IoMT). We present a system design which guarantees secure data exchange, reliable model aggregation and traceability. Additionally, We will also discuss about challenges and ethical consideration in its implementation.
Keywords Blockchain, Federated Learning, IoMT, Healthcare 5.0, Data Privacy
Field Medical / Pharmacy
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-11-25
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.61686
Short DOI https://doi.org/hbcnt6
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