Smart Contract-Driven Pandemic Management Using Blockchain Technology and Artificial Intelligence

Abstract

The COVID-19 epidemic has negatively affected features of human beings and diverse sectors, particularly the healthcare industry. This modality led to the formation of novel life patterns that people need to face to reduce the spreading of the pandemic by promising social distance, amongst others. For that reason, investigators have discovered several deep learning (DL) and machine learning (ML) based techniques to quickly diagnose COVID-19 patients using X-ray images. ML-based approaches can decrease costs and take less time for treatment. Nevertheless, maintaining patient privacy poses challenges inside such third-person-controlled models, potentially decreasing to protect patients from possible discomfort and disgrace. However, BC technology provides the potential to safely store complex HealthCare data anonymously, without needing third-person interference. In this study, we introduced a Leveraging Blockchain Technology and Artificial Intelligence using a Smart Contract-Driven COVID-19 Pandemic Detection (LBCTAI-SCCPD) model. The main aim of the LBCTAI-SCCPD model is to investigate the absence or presence of COVID-19 from medical images. To accomplish that, the LBCTAI-SCCPD model is a blockchain-based COVID-19 recognition infrastructure, which contains a smart contracting method for uploading COVID-19-positive case-oriented information with blockchain. At the initial step, the LBCTAI-SCCPD technique employs an adaptive median filtering (AMF) approach to pre-process the input image. In addition, the complex patterns and features in the images can be derived from CapsNet model. Furthermore, the radial basis function neural network (RBFNN) model can be used for a precise COVID-19 process of classification. Lastly, the dung beetle optimization (DBO) algorithm is used for optimal hyperparameter selection of the RBFNN model. To demonstrate the better performance of the LBCTAI-SCCPD technique, a sequence of simulations is executed on the benchmark dataset. The stimulated outcomes stated the improved results of the LBCTAI-SCCPD system on the other techniques.