COVID-19 and artificial intelligence: protecting health-care workers and curbing the spread

Abstract

Confirmed cases of coronavirus disease 2019 (COVID-19) exceed those of severe acute respiratory syndrome (SARS), and, at time of publication, now stand at over 73,435 confirmed cases and over 2000 deaths globally, nearly all in China. By comparison, SARS killed 774 people in 2003, again mostly in China, the epicentre of both outbreaks. Both COVID-19 and SARS spread across continents, infect animals and humans, and use similar mechanics to enter and infect the cell. On the frontline, tactical response to COVID-19 is similar to that of SARS but one major difference exists: in the 17 years since SARS, a powerful new tool has emerged that could potentially be instrumental in keeping this virus within reasonable limits—namely, artificial intelligence (AI).

Cited by papers we hold 7

• Application of Telemedicine in COVID-19: A Bibliometric Analysis · 2022
  Not checked
• A Review on Deep Learning Techniques for the Diagnosis of Novel Coronavirus (COVID-19) · 2021
  No notice
• Novel Coronavirus Infection (COVID-19) in Humans: A Scoping Review and Meta-Analysis · 2020
  No notice
• Telehealth in the Context of COVID-19: Changing Perspectives in Australia, the United Kingdom, and the United States · 2020
  No notice
• How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic · 2020
  No notice
• Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatment · 2020
  No notice
• Digital Response During the COVID-19 Pandemic in Saudi Arabia · 2020
  No notice

Reads

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.