Accessibility settings

This paper is in the following e-collection/theme issue:

Artificial Intelligence (2355) Clinical Information and Decision Making (2073) Machine Learning (2235) Coronary Heart Disease (114) Congenital Heart Disease (11) Cardiac Diagnostics (36) New Diagnostic Tools and Instruments for Pediatrics (51) Screening and Early Diagnosis in Pediatrics (41) Computer-Aided Diagnosis (278) mHealth for Diagnosis (85) Digital Health Reviews (1829)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57641, first published .
Accuracy of Machine Learning in Discriminating Kawasaki Disease and Other Febrile Illnesses: Systematic Review and Meta-Analysis

Accuracy of Machine Learning in Discriminating Kawasaki Disease and Other Febrile Illnesses: Systematic Review and Meta-Analysis

Accuracy of Machine Learning in Discriminating Kawasaki Disease and Other Febrile Illnesses: Systematic Review and Meta-Analysis

Authors of this article:

Jinpu Zhu1 Author Orcid Image ;   Fushuang Yang2 Author Orcid Image ;   Yang Wang3 Author Orcid Image ;   Zhongtian Wang1 Author Orcid Image ;   Yao Xiao1 Author Orcid Image ;   Lie Wang2 Author Orcid Image ;   Liping Sun2 Author Orcid Image
Article Authors Cited by (8) Tweetations Metrics

Journals

  1. Gu T, Pan W, Yu J, Ji G, Meng X, Wang Y, Li M. Mitigating bias in AI mortality predictions for minority populations: a transfer learning approach. BMC Medical Informatics and Decision Making 2025;25(1) View
  2. Mirata D, Tiezzi A, Buffoni L, Pagnini I, Maccora I, Marrani E, Mastrolia M, Simonini G, Giani T. Learning-Based Models for Predicting IVIG Resistance and Coronary Artery Lesions in Kawasaki Disease: A Review of Technical Aspects and Study Features. Pediatric Drugs 2025;27(4):465 View
  3. Moncur C, Kamotho M, Jain T, Weslock N, Ragheb M, Mitchell K. Early life exposure to ambient particulate matter and Kawasaki disease: a systematic review and meta-analysis. Frontiers in Cardiovascular Medicine 2025;12 View
  4. Martel M, José-Garcia A, Vens C, De Vos M, Sobanski V. Artificial intelligence for precision medicine. Therapies 2026;81(2):171 View
  5. Xue X, Dai G, Lin Y, He L, Sheng W, Sun J, Liu F. Ferroptosis-related oxidative stress activation in the acute phase of Kawasaki disease. Frontiers in Immunology 2025;16 View
  6. Li Y, Zhao K, Wu J. Machine Learning in Left Ventricular Hypertrophy Detection: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2026;28:e76637 View

Conference Proceedings

  1. Raju K, Thirupathi V. 2026 International Conference on AI-Driven Smart Systems and Ubiquitous Computing (ICAUC). Enhanced Kawasaki Disease Diagnosis using a Feature-Optimized Ensemble Model with Modified Grey Wolf Optimization View
  2. Raju K, Thirupathi V. 2026 5th International Conference on Communication, Computing and Electronics Systems (ICCCES). An Explainable AdaBoost Framework for Early Kawasaki Disease Detection Using Bat Algorithm Based Feature Optimization View