As the Covid-19 crisis continues to spread its tentacles across the globe, the magic of artificial intelligence continues to spread too. Top AI minds have put their heads together to devise effective means to battle the uncontrollable virus, and the results have been very promising. From developing new ways to detect the infection to helping with drug discovery, artificial intelligence and machine learning have provided humans with protective armour against the deadly virus. Discussed here are some useful research outputs from top global universities.

• An ML system for finding Covid-19 treatment options for elderly patients: A research team at MIT’s Department of Electrical Engineering and Computer Science has developed a machine learning-based approach to identify drugs already on the market that could potentially be repurposed to fight Covid-19, particularly in the elderly. The system accounts for changes in gene expression in lung cells caused by both the disease and aging. That combination could allow medical experts to more quickly seek drugs for clinical testing in elderly patients, who tend to experience more severe symptoms. The researchers pinpointed the protein RIPK1 as a promising target for Covid-19 drugs, and they identified three approved drugs that act on the expression of RIPK1. Read more...
• Epidemiological modelling for tracking the virus: The Delphi Research Group at Carnegie Mellon University has made the epidemiological tool COVIDcast for tracking COVID-19. The group has worked with industry partners to evaluate large databases to track illness, monitor mask wearing and explore vaccine hesitancy across the United States. Working in close partnership with the CDC, the research team from the Statistics & Data Science and Machine Learning departments at CMU made it possible to dig into the granularity of data at the county level and lower, allowing them to view changes that could be impactful for public health. Read more...
• The neural network COVID-Net can help spot Covid-19 from chest X-rays: COVID-Net is a deep convolutional neural network design tailored for the detection of COVID-19 cases from chest radiography images that are open source and available to the general public. It is developed by Linda Wang and Alexander Wong from the University of Waterloo and DarwinAI in Canada. Read more...
• Using AI for a better COVID-19 prediction model: A team of Caltech students have developed a tool, called CS156, for policymakers to assess the pandemic's potential impact on their community and to predict the effect of mitigation efforts. With the use of AI, it is possible to discover patterns hidden in data that humans alone might not recognize. Read more...

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