Federated Learning Model for Healthchain System
R. Durga, Eswaran Poovammal · 2021
Global pandemic has emphasized the need for healthcare information processing capabilities even while pushing data privacy, openness, and consent to the forefront. The pandemic has revealed the limitations of employing existing digital healthcare technology to handle public health emergencies. As a result of the pandemic scenario, research institutes and governments have been compelled to reconsider healthcare delivery methods in order to maintain service continuity. Researchers have been looking at ways to improve the digital health workflow with disruptions such as decentralized artificial system. Disintermediate blockchain technology and federated learning are powerful solutions that can address these problems. The federated learning technique which enables data to be shared for better predictions while maintaining data openness based on authentication. Thus, to attain high accuracy in prediction and to enhance the security and privacy in healthcare, a disintermediate intelligent system is investigated with advanced learning model called federated learning model.