In machine learning, a computer sifts through vast amounts of data to look for patterns. In this groundbreaking study, NIH-supported researchers led by Emily Pfaff, University of North Carolina, Chapel Hill, and Melissa Haendel, the University of Colorado Anschutz Medical Campus, Aurora, relied on machine learning. The results, though still preliminary and in need of further validation, point the way to developing a fast, easy-to-use computer algorithm to help determine whether a person with a positive COVID test is likely to battle Long COVID. Researchers found that computers, after scanning thousands of electronic health records (EHRs) from people with Long COVID, could reliably make the call. But a recent study, published in the journal Lancet Digital Health, shows that a well-trained computer and its artificial intelligence can help. The variability also makes it difficult to identify all those who have Long COVID, whether they realize it or not. But because Long COVID is so variable from person to person, it’s extremely difficult to work backwards and determine what these people had in common that might have made them susceptible to Long COVID. People understandably want answers to help them manage this complex condition referred to as Long COVID syndrome.
These symptoms run the gamut including fatigue, shortness of breath, brain fog, anxiety, and gastrointestinal trouble. One of the most puzzling is why many people who get over an initial and often relatively mild COVID illness later develop new and potentially debilitating symptoms. The COVID-19 pandemic continues to present considerable public health challenges in the United States and around the globe. Posted on June 7th, 2022 by Lawrence Tabak, D.D.S., Ph.D. Using AI to Advance Understanding of Long COVID Syndrome