Shows >89% accuracy for a machine learning model predicting Kawasaki disease across three pediatric hospitals, highlighting its potential as a physician support tool.
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.
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Lam et al. (2025) studied this question.
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