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

Authors :
Hai, Tao
Zhou, Jincheng
Srividhya, S. R.
Jain, Sanjiv Kumar
Young, Praise
Agrawal, Shweta
Source :
Journal of Cloud Computing (2192-113X); 7/28/2022, Vol. 11 Issue 1, p1-11, 11p
Publication Year :
2022

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
2192113X
Volume :
11
Issue :
1
Database :
Complementary Index
Journal :
Journal of Cloud Computing (2192-113X)
Publication Type :
Academic Journal
Accession number :
158238700
Full Text :
https://doi.org/10.1186/s13677-022-00294-6