TY - JOUR
AU - Mantey, Eric Appiah
AU - Zhou, Conghua
AU - Mani, Vinodhini
AU - Ibeke, Ebuka
AU - Arthur, John Kingsley
PY - 2022
DA - April
TI - Maintaining privacy for a recommender system diagnosis using blockchain and deep learning.
JO - Human-centric Computing and Information Sciences
AB - The healthcare sector has been revolutionized by Blockchain and AI technologies. Artificial intelligence uses algorithms, recommender systems, decision-making abilities, and big data to display a patient's health records using blockchain. Healthcare professionals can make use of Blockchain to display a patient's medical records with a secured medical diagnostic process. Traditionally, data owners have been hesitant to share medical and personal information due to concerns about privacy and trustworthiness. Using Blockchain technology, this paper presents an innovative model for integrating healthcare data sharing into a recommender diagnostic computer system. Using the model, medical records can be secured, controlled, authenticated, and kept confidential. In this paper, researchers propose a framework for using the Ethereum Blockchain and x-rays as a mechanism for access control, establishing hierarchical identities, and using pre-processing and deep learning to diagnose COVID-19. Along with solving the challenges associated with centralized access control systems, this mechanism also ensures data transparency and traceability, which will allow for efficient diagnosis and secure data sharing.
PB - KIPS-CSWRG
UR - https://rgu-repository.worktribe.com/output/1645830
KW - Coronavirus (COVID-19)
ER