![]() ![]() They fed that EHR data into a computer, along with health information from almost 600 patients who’d been seen at a Long COVID clinic. Next, they examined common features, including any doctor visits, diagnoses, or medications, from the group’s roughly 100,000 adults. The researchers defined a group of more than 1.5 million adults in N3C who either had been diagnosed with COVID-19 or had a record of a positive COVID-19 test at least 90 days prior. It is part of NIH’s Researching COVID to Enhance Recovery (RECOVER) initiative, which aims to improve understanding of Long COVID. (The records are de-identified to protect patient privacy.) The researchers found just what they needed in the National COVID Cohort Collaborative (N3C), a national, publicly available data resource sponsored by NIH’s National Center for Advancing Translational Sciences. In this case, Pfaff, Haendel, and team decided to “train” their computer on EHRs from people who had reported a COVID-19 infection. As such, machine learning can pick up on subtle patterns that people would otherwise miss. One reason machine learning is so powerful is that it doesn’t require humans to tell the computer which features it should look for. 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
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |