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Using AI tool based to predict the adverse effect of COVID-19

Weekly Musings In The World Of AI
Weekly Musings In The World Of AI
The symptoms and side effects of COVID-19 are scattered across a diagnostic spectrum. Some patients are asymptomatic or experience only minor immune responses, while others report significant long-term illnesses lasting complications that may lead to fatal outcomes.

Three researchers from the Georgia Institute of Technology and one from Emory University are trying to help clinicians sort through these factors and the spectrum of patient outcomes by equipping healthcare professionals with a new “decision prioritization tool.”
The team’s new artificial intelligence-based tool helps clinicians understand and better predict which adverse effects their Covid-19 patients could experience, based on comorbidities and current side effects -; and, in turn, also helps suggest specific Food and Drug Administration-approved (FDA) drugs that could help treat the disease and improve patient health outcomes. The researcher’s latest findings are the focus of a new study published October 21 in Scientific Reports.
“Humans are molecular machines, and presumably there are biological and physical rules to dictate our responses,” said Skolnick. “We basically built an AI-based approach which was designed given the interactive set of proteins in humans which interact with the [novel] coronavirus,” he adds. “We then asked ourselves, ‘Could we predict, based on biochemical pathways, which interactive proteins are associated with side effects?’”
Joining Skolnick from the School of Biological Sciences are Ph.D. student Courtney Astore and senior research scientist Hongyi Zhou, both from the Center for the Study of Systems Biology. Joshy Jacob of the Department of Microbiology and Immunology in the Emory Vaccine Center at the Emory School of Medicine also worked on the study.
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