AI-based Power Screening Solution for SARS-CoV2 Infection: A Sociodemographic Survey and COVID-19 Cough Detector

Globally, the confirmed coronavirus (SARS-CoV2) cases are being increasing day by day. Coronavirus (COVID-19) causes an acute infection in the respiratory tract that started spreading in late 2019. Huge datasets of SARS-CoV2 patients can be incorporated and analyzed by machine learning strategies for understanding the pattern of pathological spread and helps to analyze the accuracy and speed of novel therapeutic methodologies, also detect the susceptible people depends on their physiological and genetic aspects. To identify the possible cases faster and rapidly, we propose the Artificial Intelligence (AI) power screening solution for SARS- CoV2 infection that can be deployable through the mobile application. It collects the details of the travel history, symptoms, common signs, gender, age and diagnosis of the cough sound. To examine the sharpness of pathomorphological variations in respiratory tracts induced by SARS-CoV2, that compared to other respiratory illnesses to address this issue. To overcome the shortage of SARS-CoV2 datasets, we apply the transfer learning technique. Multipronged mediator for risk-averse Artificial Intelligence Architecture is induced for minimizing the false diagnosis of risk-stemming from the problem of complex dimensionality. This proposed application provides early detection and prior screening for SARS-CoV2 cases. Huge data points can be processed through AI framework that can examine the users and classify them into "Probably COVID", "Probably not COVID" and "Result indeterminate".