Machine-learning tool diagnoses complex pediatric inflammatory diseases

A Cornell-led team developed machine-learning models using cell-free RNA to diagnose challenging pediatric inflammatory diseases, including Kawasaki disease and Multisystem Inflammatory Syndrome in Children. The study analyzed 370 plasma samples, demonstrating the tool's ability to identify conditions and monitor organ health. Published on September 6 in the Proceedings of the National Academy of Sciences, the research was supported by the NIH and involved multiple institutions.