BVFLEMR: an integrated federated learning and blockchain technology for cloud-based medical records recommendation system

【Author】 Hai, Tao; Zhou, Jincheng; Srividhya, S. R.; Jain, Sanjiv Kumar; Young, Praise; Agrawal, Shweta

【Source】JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS

【影响因子】3.418

【Abstract】Blockchain is the latest boon in the world which handles mainly banking and finance. The blockchain is also used in the healthcare management system for effective maintenance of electronic health and medical records. The technology ensures security, privacy, and immutability. Federated Learning is a revolutionary learning technique in deep learning, which supports learning from the distributed environment. This work proposes a framework by integrating the blockchain and Federated Deep Learning in order to provide a tailored recommendation system. The work focuses on two modules of blockchain-based storage for electronic health records, where the blockchain uses a Hyperledger fabric and is capable of continuously monitoring and tracking the updates in the Electronic Health Records in the cloud server. In the second module, LightGBM and N-Gram models are used in the collaborative learning module to recommend a tailored treatment for the patient's cloud-based database after analyzing the EHR. The work shows good accuracy. Several metrics like precision, recall, and F1 scores are measured showing its effective utilization in the cloud database security.

【Keywords】Collaborative learning; Federated learning; Recommendation system; Blockchain; Cloud security; EHR

【发表时间】2022 28-Jul

【收录时间】2022-08-15

【文献类型】实验仿真

【主题类别】

区块链技术-协同技术-物联网