External Validation of a Machine Learning Model to Diagnose Kawasaki Disease

Jonathan Y Lam¹, Chisato Shimizu², Michael A Gardiner², Thomas Giorgio³, Veronique Wright³, Annette Baker³, Marsha S Anderson⁴, Heather Heizer⁵, Sindhu Mohandas⁶, Alicia Kazarians⁷, Kelli Kaneta⁸, Pei-Ni Jone⁹, Samuel R Dominguez⁴, Jacqueline R Szmuszkovicz¹⁰, Jane W Newburger³, Adriana H Tremoulet², Jane C Burns¹¹

Affiliations

¹ Department of Biomedical Informatics, University of California San Diego, La Jolla, CA.
² Department of Pediatrics, Rady Children's Hospital and University of California San Diego, San Diego, CA.
³ Department of Cardiology, Boston Children's Hospital, Boston, MA.
⁴ Department of Pediatrics, Children's Hospital Colorado and University of Colorado School of Medicine, Aurora, CO.
⁵ Department of Pediatric Infectious Diseases, Oklahoma Children's Hospital and University of Oklahoma Health Science Center, Oklahoma City, OK.
⁶ Division of Infectious Disease, Children's Hospital Los Angeles and Keck School of Medicine of the University of Southern California, Los Angeles, CA.
⁷ Division of Cardiology, Children's Hospital Los Angeles, Los Angeles, CA.
⁸ Division of Nephrology, Children's Hospital Los Angeles, Los Angeles, CA.
⁹ Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, IL.
¹⁰ Division of Cardiology, Children's Hospital Los Angeles and Keck School of Medicine of the University of Southern California, Los Angeles, CA.
¹¹ Department of Pediatrics, Rady Children's Hospital and University of California San Diego, San Diego, CA. Electronic address: jcburns@health.ucsd.edu.

PMID: 40122277
DOI: 10.1016/j.jpeds.2025.114543

Free article

Multicenter Study

External Validation of a Machine Learning Model to Diagnose Kawasaki Disease

Jonathan Y Lam et al. J Pediatr. 2025 Jul.

Free article

. 2025 Jul:282:114543.

doi: 10.1016/j.jpeds.2025.114543. Epub 2025 Mar 21.

Authors

Affiliations

¹ Department of Biomedical Informatics, University of California San Diego, La Jolla, CA.
² Department of Pediatrics, Rady Children's Hospital and University of California San Diego, San Diego, CA.
³ Department of Cardiology, Boston Children's Hospital, Boston, MA.
⁴ Department of Pediatrics, Children's Hospital Colorado and University of Colorado School of Medicine, Aurora, CO.
⁵ Department of Pediatric Infectious Diseases, Oklahoma Children's Hospital and University of Oklahoma Health Science Center, Oklahoma City, OK.
⁶ Division of Infectious Disease, Children's Hospital Los Angeles and Keck School of Medicine of the University of Southern California, Los Angeles, CA.
⁷ Division of Cardiology, Children's Hospital Los Angeles, Los Angeles, CA.
⁸ Division of Nephrology, Children's Hospital Los Angeles, Los Angeles, CA.
⁹ Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, IL.
¹⁰ Division of Cardiology, Children's Hospital Los Angeles and Keck School of Medicine of the University of Southern California, Los Angeles, CA.
¹¹ Department of Pediatrics, Rady Children's Hospital and University of California San Diego, San Diego, CA. Electronic address: jcburns@health.ucsd.edu.

PMID: 40122277
DOI: 10.1016/j.jpeds.2025.114543

Abstract

We investigated the generalizability of a machine learning model trained to predict Kawasaki disease using laboratory and clinical data. The algorithm performed with >89% accuracy at 3 children's hospitals across the United States, demonstrating its potential as a physician support tool for diagnosing Kawasaki disease.

Keywords: Kawasaki disease; machine learning.

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Conflict of interest statement

Declaration of Competing Interest This work was funded by a grant from the Gordon and Marilyn Macklin Foundation. All authors declare no conflict of interest.

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External Validation of a Machine Learning Model to Diagnose Kawasaki Disease

Affiliations

External Validation of a Machine Learning Model to Diagnose Kawasaki Disease

Authors

Affiliations

Abstract

Conflict of interest statement

Publication types

MeSH terms

LinkOut - more resources

Full Text Sources

Medical