An Adaptive Cloud and Internet of Things-Based Disease Detection Approach for Secure Healthcare system
Abstract
The role of the Internet of Things (IoT) in disease data handling, analysis, prediction, and classification is prominent due to digital electronic healthcare records (EHRs). This article introduces a secure EHR handling scheme for disease detection and classification from the observed data. First, the data transmission is secured through forward two-way authentication and its integrity is verified on the receiving end. The extracted EHR data is correlated with the clinical observations to detect the disease. This scheme therefore relies on maximum data integrity to ensure high disease detection through uninterrupted patient data transmission. As a result, the proposed scheme enhanced the integrity verification by 14.31% and increased the accuracy of disease detection by 11.73% across various accumulation periods. The data correlation and transmission are verified and validated using IoT and its associated technologies for improving the disease detection ratio.