External Validation of a Machine Learning Model to Diagnose Kawasaki Disease

We investigated the generalizability of a machine learning model trained to predict Kawasaki disease using laboratory and clinical data. The algorithm performed with >89% accuracy at 3 children's hospitals across the United States, demonstrating its potential as a physician support tool for diagnosing Kawasaki disease.