Coronary Artery Brightness on Echocardiography as a Novel Marker in Kawasaki Disease ― Machine Learning-Based Cluster Analysis ―
Quantitative CAB analysis combined with unsupervised ML effectively stratified KD patients into subgroups with distinct coronary and biomarker profiles. This method may serve as a novel non-invasive tool to evaluate disease severity and predict IVIG resistance in acute-phase KD.
Authors
- Takamichi Ishikawa (ORCID: https://orcid.org/0000-0002-7118-3014)
- Makoto Watanabe (ORCID: https://orcid.org/0000-0002-0734-4047)
- Ryuji Fukazawa (ORCID: https://orcid.org/0000-0003-1841-233X)
- Isao Miyairi (ORCID: https://orcid.org/0000-0003-3886-9089)
- Yoshifumi Miyagi
- Yukako Yoshikane
- Satoru Iwashima (ORCID: https://orcid.org/0000-0003-2713-321X)
- Toshimichi Yoshida (ORCID: https://orcid.org/0000-0001-8935-8217)
- Daisuke Masui
Institutions
- Mie University (JP)
- Hamamatsu University School of Medicine (JP)
- Fukuoka University (JP)
- Yokufukai Hospital (JP)
- Haibara General Hospital (JP)
- Mie Chuo Medical Center (JP)
- Nippon Medical School (JP)
Publication Details
- Journal
- Circulation Reports
- Published
- 2025-12-12
- DOI
- https://doi.org/10.1253/circrep.cr-25-0247
- Primary Topic
- Kawasaki Disease and Coronary Complications
- Type
- article
- Field-Weighted Citation Impact
- 0.00