Development of a machine learning-based predictive nomogram for screening children with juvenile idiopathic arthritis: a pseudo-longitudinal study of 223,195 children in the United States.

Journal: Frontiers in public health
Published Date: May 29, 2025

Abstract

BACKGROUND: Juvenile idiopathic arthritis (JIA) is a prevalent chronic rheumatological condition in children, with reported prevalence ranging from 12. 8 to 45 per 100,000 and incidence rates from 7.8 to 8.3 per 100,000 person-years. The diagnosis of JIA can be challenging due to its symptoms, such as joint pain and swelling, which can be similar to other conditions (e.g., joint pain can be associated with growth in children and adolescents).

Authors

  • Yu-Sheng Lee
    School of Integrated Sciences, Sustainability, and Public Health, College of Health, Science, and Technology, University of Illinois Springfield, Springfield, IL, United States.
  • Kira Gor
    School of Integrated Sciences, Sustainability, and Public Health, College of Health, Science, and Technology, University of Illinois Springfield, Springfield, IL, United States.
  • Matthew Evan Sprong
    Department of Addictions Studies and Behavioral Health, College of Health and Human Services, Governors State University, University Park, IL, United States.
  • Junu Shrestha
    School of Integrated Sciences, Sustainability, and Public Health, College of Health, Science, and Technology, University of Illinois Springfield, Springfield, IL, United States.
  • Xueli Huang
    Department of Computer Science, College of Health, Science, and Technology, University of Illinois Springfield, Springfield, IL, United States.
  • Heaven Hollender
    School of Health and Human Sciences, Indiana University Indianapolis, Indianapolis, IN, United States.

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