A Federated Learning and Blockchain Framework for IoMT-Driven Healthcare 5.0
R. D. St. Denis, N. Venkateswaran, S. Gangadharan, M. Shunmugasundaram, Guduri Chitanya, Girija M. S, V. V. Satyanarayana Tallapragada, R.G. Vidhya · International Journal of Basic and Applied Sciences · 2025
This paper presents an innovative framework integrating federated learning, blockchain, and the Internet of Medical Things (IoMT) to revolutionize healthcare systems in the context of Healthcare 5.0. By harnessing advanced sensors and leveraging 5G technology, the framework enables continuous, real-time data collection and intelligent analysis, facilitating highly personalized and timely medical interventions. Federated learning enables decentralized model training across edge devices, preserving data privacy and enhancing security. Simultaneously, blockchain ensures the integrity and transparency of healthcare records through a decentralized and tamper-proof ledger. The synergy of these technologies fosters secure and efficient communication across a network of interconnected medical devices. This framework significantly enhances healthcare delivery by promoting proactive, patient-focused, and adaptive care models. Additionally, IoMT expands the capabilities of medical equipment by enabling remote monitoring, automated data transmission, and comprehensive patient oversight. As the vision of Healthcare 5.0 progresses, embracing such cutting-edge technological solutions is vital for improving patient outcomes, streamlining operations, and accelerating medical innovation. Through the combined power of federated learning, blockchain, and IoMT, the healthcare sector stands on the brink of a transformative shift toward secure, intelligent, and personalized care.