Machine Learning Tackles Long COVID - Rehab Management

A new machine learning tool aims to help scientists investigate why some people develop long COVID, a series of debilitating, chronic symptoms that last months to years after the initial COVID-19 infection. Developed by a team of researchers from institutions across the country, led by Justin Reese of Berkeley Lab and Peter Robinson of Jackson Lab, the software analyzes entries in electronic health records (EHRs) to find symptoms in common between people who have been diagnosed with long COVID and to define subtypes of the condition. The research, which is described in a new paper in eBioMedicine, also identified strong correlations between different long COVID subtypes and pre-existing conditions such as diabetes and hypertension. According to Reese, a computer research scientist in Berkeley Lab's Biosciences Area, this research will help improve our understanding of how and why some individuals develop long COVID symptoms and may enable more effective treatments by helping clinicians develop tailored therapies for each group. For example, the best treatment for patients experiencing nausea and abdominal pain might be quite different from a treatment for those suffering from persistent cough and other lung symptoms.