Covid 19 Detection, Flow Mitigation and Hospital Care

  • Manas Ranjan Sahoo, Prasenjit Maiti
Keywords: Deep Learning, Healthcare, Drug Development, Predictive Analysis, Diagnosis, Image Classification


COVID-19 was first detected in Dec 2019 and has since spread exponentially across the planet, infecting tens of millions of participants. The infection is lethal, and those who have had previous illnesses or are above the age of 60 are at a greater risk of dying. The healthcare sector sectors have accelerated their efforts to discover a solution, and several measures have been altered to slow the virus's propagation. Although machine learning (ML) approaches have been commonly utilized in other fields, there is now a huge market for ML-assisted diagnostic systems for sampling, monitoring, and projecting the spread of COVID-19, as well as seeking a cure. In this article, we take a look at how machine learning has aided in the fight against the virus so far, focusing on sampling, modeling, and vaccine growth. We provide a concise overview of the machine learning methods and prototypes and can be used on this mission to help combat the virus.

How to Cite
Manas Ranjan Sahoo, Prasenjit Maiti. (2021). Covid 19 Detection, Flow Mitigation and Hospital Care. Design Engineering, 960 -.