Fusion Optimization and Classification Model for Blockchain Assisted Healthcare Environment

Abstract

Healthcare transformation is becoming one of the highest priorities in a world whereby remarkable advances in technology are taking place. Recent healthcare data fusion management systems are centralized, which possess the probability of failure in case of a natural disaster. Blockchain has expanded fast to be the most widely spoken innovation that could address a large number of present data management problems in the health care sector. The usage of blockchain technology for the distribution of secure and safe health care datasets has received all the attention. This article presents a Bat Optimization Algorithm with Fuzzy Neural Network Based Classification (BOA-FNNC) Model for Blockchain Assisted Healthcare Data Fusion Environment. The presented BOA-FNNC technique mainly focuses on achieving security in the healthcare sector using BC technology. For accomplishing this, the BOA-FNNC technique performs BC assisted data transmission in the medical sector. Besides, the VGG-16 model is exploited for the creation of feature vectors. To classify healthcare data, the BOA with FNN model is utilized in this study, where the BOA fine tune the parameters related to the FNN model which in turn boosts the classifier efficiency. For illustrating the betterment of the BOA-FNNC technique, a series of experiments were performed. The comparison study reported the enhancements of the BOA-FNNC technique over other recent approaches.