Development and validation of an explainable machine learning-based prediction model for primary Kawasaki disease complicated with coronary artery aneurysms
The XGBoost algorithm-based explainable model might be used to predict the occurrence of CAA in children with KD.
Authors
- Dong Liu (ORCID: https://orcid.org/0000-0003-2375-5716)
- Huiyun Ming
- Zi‐Xia Song (ORCID: https://orcid.org/0000-0001-6183-0110)
- Bin Liu (ORCID: https://orcid.org/0000-0003-0208-6066)
Institutions
- Affiliated Hospital of Southwest Medical University (CN)
Publication Details
- Journal
- Translational Pediatrics
- Published
- 2025-02-01
- DOI
- https://doi.org/10.21037/tp-24-359
- Primary Topic
- Kawasaki Disease and Coronary Complications
- Type
- article
- Field-Weighted Citation Impact
- 0.00