Prediction of coronary artery lesions in children with Kawasaki syndrome based on machine learning

Abstract Objective Kawasaki syndrome (KS) is an acute vasculitis that affects children < 5 years of age and leads to coronary artery lesions (CAL) in about 20-25% of untreated cases. Machine learning (ML) is a branch of artificial intelligence (AI) that integrates complex data sets on a large scale...

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Autori principali:	Yaqi Tang, Yuhai Liu, Zhanhui Du, Zheqi Wang, Silin Pan
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	BMC 2024-03-01
Serie:	BMC Pediatrics
Soggetti:	Kawasaki syndrome Coronary artery lesions Machine learning Random forest
Accesso online:	https://doi.org/10.1186/s12887-024-04608-2
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