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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| Hauptverfasser: | , , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
BMC
2024-03-01
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| Schriftenreihe: | BMC Pediatrics |
| Schlagworte: | |
| Online-Zugang: | https://doi.org/10.1186/s12887-024-04608-2 |
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