Efficient COVID-19 testing via contextual model based compressive sensing.

ABSTRACT: The COVID-19 pandemic is threatening billions of people's life all over the world. As of March 6, 2021, covid-19 has confirmed in 115,653,459 people worldwide. It has also a devastating effect on businesses and social activities. Since there is still no definite cure for this disease, extensive testing is the most critical issue to determine the trend of illness, appropriate medical treatment, and make social distancing policies. Besides, testing more people in a shorter time helps to contain the contagion. The PCR-based methods are the most popular tests which take about an hour to make the output result. Obviously, it makes the number of tests highly limited and consequently, hurts the efficiency of pandemic control. In this paper, we propose a new approach to identify affected individua

SUBMITTER: Hasaninasab M 

PROVIDER: S-EPMC8362654 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature