Using machine learning models based on cardiac magnetic resonance parameters to predict the prognostic in children with myocarditis
ML models, particularly the LR model, demonstrate the potential to predict the prognosis of children with myocarditis. These findings provide valuable insights for cardiologists, supporting more informed clinical decision-making and potentially enhancing patient outcomes in pediatric myocarditis cases.
Authors
- Shenghong Ju (ORCID: https://orcid.org/0000-0001-5041-7865)
- Wan‐liang Guo (ORCID: https://orcid.org/0000-0003-3849-2904)
- Xueke Zhang (ORCID: https://orcid.org/0000-0003-4195-6490)
- Dongliang Hu
- Yuanyuan Wu (ORCID: https://orcid.org/0000-0001-8884-0802)
- Duchang Zhai
- Guohua Fan (ORCID: https://orcid.org/0000-0001-5806-7177)
- Yan Liu (ORCID: https://orcid.org/0000-0002-4672-1837)
- Wu Cai (ORCID: https://orcid.org/0000-0002-6800-4177)
- M. Cui (ORCID: https://orcid.org/0009-0009-0431-2283)
Institutions
- Soochow University (CN)
- Zhongda Hospital Southeast University (CN)
- Second Affiliated Hospital of Soochow University (CN)
Publication Details
- Journal
- BMC Pediatrics
- Published
- 2025-05-23
- DOI
- https://doi.org/10.1186/s12887-025-05753-y
- Citations
- 4
- Primary Topic
- Viral Infections and Immunology Research
- Type
- article
- Field-Weighted Citation Impact
- 5.55
Funders
- Soochow University
- State Key Laboratory of Radiation Medicine and Protection