Artificial Intelligence during a pandemic: The COVID ‐19 example

Sathian Dananjayan, Gerard Marshall Raj

First published: 20 May 2020


After 2000, the pandemics are testing the AI’s ability to handle extreme events. The two major factors affecting AI algorithms include the availability of historical and real‐time data and high computational power.

WHO and CDC (United States) are receiving data of several diseases and situations occurring across the world. With modern computer architecture and internet, all these data can be accessed in real‐time by different institutes to develop an autonomous or collaborative AI model to handle various tasks. In addition to the official data, AI can gather information from news outlets, forums, healthcare reports, travel data, social media posts, and others in multiple languages across the world by using natural language processing (NLP) techniques and flag their priority.

Some noticeable examples of AI that are used to battle the COVID‐19 pandemic and others are as follows:

  • AI can be used as an early outbreak warning system, BlueDot, an AI‐driven algorithm not only successfully detected the outbreak of Zika virus in Florida but also spotted COVID‐19, 9 days before the WHO released its statement alerting people to the emergence of a novel coronavirus.
  • Researchers from the Huazhong University of Science and Technology (HUST) and Tongji Hospital in Wuhan, Hubei have developed an AI diagnostic tool (XGBoost machine learning‐based prognostic model) that can quickly analyse blood samples to predict survival rates of COVID‐19 infected patients and it turns out to be 90% accurate.
  • In Wuhan, China, an AI diagnostic tool is used to distinguish COVID‐19 from other types of pneumonia within seconds by analysing patients’ chest CT scan images. The authors claimed that their new model holds great potential to relieve the pressure off frontline radiologists, improve early diagnosis, isolation and treatment, and thus contribute to the control of the epidemic.
  • COVID‐Net, a deep learning model is designed to detect the COVID‐19 positive cases from chest X‐rays and accelerate treatment for those who need it the most.
  • Google’s DeepMind is helping scientist to study various features of the SARS‐CoV‐2 (severe acute respiratory syndrome coronavirus 2) and has predicted the protein structure of the virus.
  • Several AI‐based computer vision camera systems are deployed in China and across the world to scan crowds for COVID‐19 symptoms and monitor people during lockdown.
  • FluSense, a contactless syndromic surveillance platform, is used to forecast seasonal flu and other viral respiratory outbreaks, such as the COVID‐19 pandemic or SARS.
  • Interestingly, AI‐powered autonomous service robots and humanoid robots “Cloud Ginger (aka XR‐1)” are used in hospitals at Wuhan, China. The first is used to assist the healthcare workers to deliver the foods and medicines to the patients and the latter is used to entertain the patients during quarantine


Wiley – DOI: