Diagnostic model based on bioinformatics and machine learning to distinguish Kawasaki disease using multiple datasets

Abstract excerpt

BACKGROUND: Kawasaki disease (KD), characterized by systemic vasculitis, is the leading cause of acquired heart disease in children. Herein, we developed a diagnostic model, with some prognosis ability, to help distinguish children with KD. METHODS: Gene expression datasets were downloaded from Gene Expression Omnibus (GEO), and gene sets with a potential pathogenic mechanism in KD were identified using...

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• Share to Inflammation biomarkers and pathways
• Share to Kawasaki Disease and Coronary Complications
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