This illustration, created at the Centers for Disease Control and Prevention (CDC), reveals ultrastructural morphology exhibited by the 2019 Novel Coronavirus (2019-nCoV). Note the spikes that adorn the outer surface of the virus, which impart the look of a corona surrounding the virion, when viewed electron microscopically. In this view, the protein particles E, S, M, and HE, also located on the outer surface of the particle, have all been labeled as well. This virus was identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China.

AI May Drive Faster Diagnosis of COVID-19

MedicalResearch.com Interview with:
Arni S.R. Srinivasa Rao, PhD Professor, Division of Health Economics and Modeling, DPHS Director - Laboratory for Theory and Mathematical Modeling Department of Medicine - Division of Infectious Diseases Medical College of Georgia Department of Mathematics, Augusta UniversityArni S.R. Srinivasa Rao, PhD
Professor, Division of Health Economics and Modeling, DPHS
Director – Laboratory for Theory and Mathematical Modeling
Department of Medicine – Division of Infectious Diseases
Medical College of Georgia
Department of Mathematics, Augusta University

MedicalResearch.com: What is the background for this study? What are the main findings?

Response:  This is a methodological study with a flowchart, algorithm, and theory to enable quicker identification of individuals at risk of coronavirus based on CDC’s guidelines on COVID-19. 

MedicalResearch.com: What should readers take away from your report?

Response: Mathematical principles paired with medical technology will help us better understand the severity of a virus in the population in a very timely manner. By putting good information into people’s hands, we believe it will also help our hospitals avoid being overwhelmed with people who really do not need not be there.

MedicalResearch.com: What recommendations do you have for future research as a result of this work? 

Response: I look forward to seeing how our AI system works in identifying at-risk individuals so that we can develop similar simplified methods for other diseases and viruses.

MedicalResearch.com: Is there anything else you would like to add?

Response: Science is for improving the lives of humans and other living things, and I am happy scientists are working in this direction.

Citation:

Rao, A., & Vazquez, J. (n.d.). Identification of COVID-19 Can be Quicker through Artificial Intelligence framework using a Mobile Phone-Based Survey in the Populations when Cities/Towns Are Under Quarantine. Infection Control & Hospital Epidemiology, 1-18. doi:10.1017/ice.2020.61 

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Mar 6, 2020 @ 12:25 am

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