Detecting Regions At Risk for Spreading COVID-19 Using Existing Cellular Wireless Network Functionalities The purpose of this article is to introduce a new strategy to identify areas with high human density and mobility, which are at risk of spreading COVID-19. Crowded regions with actively moving people (called at-risk regions) are […]
Deep bidirectional classification model for COVID-19 disease infected patients In December of 2019, a novel coronavirus (COVID-19) appeared in Wuhan city, China, and has been reported in many countries with millions of people infected within only four months. Chest computed tomography (CT) has proven to be a useful supplement to […]
COVID-19 Future Forecasting Using Supervised Machine Learning Models Machine learning (ML) based forecasting mechanisms have proved their significance to anticipate in perioperative outcomes to improve the decision making on the future course of actions. The ML models have long been used in many application domains which needed the identification and […]
A Weakly-supervised Framework for COVID-19 Classification and Lesion Localization from Chest CT Accurate and rapid diagnosis of COVID-19 suspected cases plays a crucial role in timely quarantine and medical treatment. Developing a deep learning-based model for automatic COVID-19 diagnosis on chest CT is helpful to counter the outbreak of SARS-CoV-2. […]
