Interpretable web-based machine learning model for predicting intravenous immunoglobulin resistance in Kawasaki disease
This region-specific, interpretable ML model ( https://milailai.shinyapps.io/data1/ ) is a practical tool for early risk stratification and personalized treatment of IVIG resistance in KD.
Authors
- Qiaobin Chen (ORCID: https://orcid.org/0000-0002-6901-4123)
- Xiaoting Lin (ORCID: https://orcid.org/0000-0002-8994-9735)
- Ying He (ORCID: https://orcid.org/0000-0003-2023-5547)
- Hongbiao Huang (ORCID: https://orcid.org/0000-0002-5420-3415)
- Meng Xiao (ORCID: https://orcid.org/0000-0001-7797-6405)
- Xin Zheng (ORCID: https://orcid.org/0000-0002-8887-4081)
- Fan Lin (ORCID: https://orcid.org/0009-0003-2210-6279)
Institutions
- Fujian Provincial Hospital (CN)
Publication Details
- Journal
- The Italian Journal of Pediatrics/Italian journal of pediatrics
- Published
- 2025-06-09
- DOI
- https://doi.org/10.1186/s13052-025-02036-1
- Citations
- 5
- Primary Topic
- Kawasaki Disease and Coronary Complications
- Type
- article
- Field-Weighted Citation Impact
- 10.03
Funders
- Natural Science Foundation of Fujian Province
- Youth and Middle-aged Scientific and Technological Innovation Leading Talents Program of the Corps