How Artificial Intelligence Can Help Us Fight the COVID-19 Pandemic

Author: Katarina Rausova

Published at: 10/27/2020

COVID-19 has brought upon us a global pandemic that dramatically influenced our lives. Fortunately, in the 21st century, we have new tools, unavailable to previous generations, which can help us fight the COVID-19 pandemic. One of them is artificial intelligence using machine learning. The global pandemic that started at the beginning of this year proved how quickly organizations can turn their machine learning expertise to help global efforts. Thanks to the machine learning expertise, the authorities can communicate with citizens more efficiently, better understand how COVID-19 spreads, and speed up the research and treatment.

Contactless screening and tracking of positive people

Many healthcare and government institutions use machine learning-powered chatbots for a contactless screening of COVID-19 symptoms and communication with citizens. These “self-triage” systems make sure that patients get their answers and the doctors spend their time treating patients with serious health conditions. One example is, a French start-up that has launched a chatbot helping people with their questions about COVID-19. The app uses real-time information from the French government and the World Health Organization and helps to assess symptoms.

Some countries use artificial intelligence in apps tracking the people who tested positive for COVID-19. One of the examples is, designed to help Danish public health authorities contain the spread of COVID-19 as the society slowly reopens. Using the app, people diagnosed with COVID-19 can easily and anonymously inform those they had been in close contact with.

Understanding how the virus spreads

Machine learning helps researchers analyze huge volumes of data and forecast the spread of COVID-19. This can provide an early warning system for future pandemics, identify the vulnerable population, and help the political leaders to make more informed decisions. One of the most successful companies in this area is BlueDot, a Canadian start-up using human and artificial intelligence to anticipate outbreaks. This company was one of the first to inform about an outbreak of a respiratory illness in Wuhan, China. Its machine learning algorithms can process news reports in 65 languages, use airline data, animal disease networks, and other data sources to detect outbreaks. Results provided by artificial intelligence are then reviewed by experts to verify that the conclusions make sense from a scientific standpoint.

Speeding up the research

Healthcare providers and researchers are faced with a massively increasing volume of information related to COVID-19. The amount of data makes it difficult to provide quick insights. One example that helps to speed up the ongoing search and research is the Artificial intelligence tool (AIM) developed by APEL in cooperation with Direct Impact. AIM uses a neural network to process research databases. The processed results are then manually checked by biochemistry experts. Since March 2020, the tool has processed tens of thousands of scientific studies and as of today (October 27), there are 997 promising substances in the free database.

Machine learning is also successfully used to help recognize patterns in radiology images to indicate the probability of disease. In UC San Diego Health, the machine learning overlays x-rays with color-coded maps that indicate pneumonia probability. This enables to speed the detection of pneumonia, a condition associated with severe COVID-19.

Machine learning can also help accelerate the discovery of drugs for COVID-19 treatment. In a project run by BenevolentAI, artificial intelligence uses data on genes, diseases, and drugs to derive the relationship between them and propose drug compounds.

These are just some of the examples of how artificial intelligence helps to fight the pandemic. One of the benefits of the current situation might be an acceleration of the Internet of Medical Things (IoMT) development and in the future, we will be better prepared for the next epidemic.