Secure blockchain enabled Cyber- Physical health systems using ensemble convolution neural network classification

【Author】 Ramanan, M.; Singh, Laxman; Kumar, A. Suresh; Suresh, A.; Sampathkumar, A.; Jain, Vishal; Bacanin, Nebojsa

【Source】COMPUTERS & ELECTRICAL ENGINEERING

【影响因子】4.152

【Abstract】Breast cancer is the most widely recognized malignancy affecting women. The risk of death has been consistently associated with breast cancer. In addition, the cyber-physical system (CPS)is the processing and data transfer of physical processes. This study presents a safe, intrusive, blockchain-based data transfer using the CPS classification model in the health industry to overcome the problem. Considering the challenges in breast tumor classification, this paper accords a reasonable arrangement to examine the mammogram image to discover the detection and classification of various stages of cancer. The breast cancer detection images obtained from the mammogram were processed and experimentally evaluated for parameters such as a sensitivity of 90%, a specificity of 98%,and a classification accuracy of 98%.The results of the ensemble convolution neural network (E-CNN) classifier, such as VGG-16 and Inception-v3, which separates ordinary and unusual cases from the applied advanced mammographic image, will be projected by comparing the two existing methods.

【Keywords】Cyber-physical system; Cybersecurity; Blockchain; Breast cancer; Malignant

【发表时间】2022 JUL

【收录时间】2022-09-15

【文献类型】实验仿真

【主题类别】

区块链应用-实体经济-医疗领域