The Florida Scoring System for stratifying children with suspected Sjögren's disease: a cross-sectional machine learning study.

Journal: The Lancet. Rheumatology
PMID: 38658114

Abstract

BACKGROUND: Childhood Sjögren's disease is a rare, underdiagnosed, and poorly-understood condition. By integrating machine learning models on a paediatric cohort in the USA, we aimed to develop a novel system (the Florida Scoring System) for stratifying symptomatic paediatric patients with suspected Sjögren's disease.

Authors

  • Wenjie Zeng
    Epidemiology, University of Florida College of Public Health and Health Professions and College of Medicine, Gainesville, FL, USA.
  • Akaluck Thatayatikom
    Pediatric Rheumatology, AdventHealth for Children, AdventHealth Medical Group, Orlando, FL, USA.
  • Nicole Winn
    Center for Orphaned Autoimmune Disorders, University of Florida College of Dentistry, Gainesville, FL, USA; Oral Medicine, Oral and Maxillofacial Diagnostic Sciences, University of Florida College of Dentistry, Gainesville, FL, USA.
  • Tyler C Lovelace
    Computational & Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
  • Indraneel Bhattacharyya
    Center for Orphaned Autoimmune Disorders, University of Florida College of Dentistry, Gainesville, FL, USA; Oral Pathology, Oral and Maxillofacial Diagnostic Sciences, University of Florida College of Dentistry, Gainesville, FL, USA.
  • Thomas Schrepfer
    Pediatric Otolaryngology, University of Florida College of Medicine, Gainesville, FL, USA.
  • Ankit Shah
    Ophthalmology, University of Florida College of Medicine, Gainesville, FL, USA.
  • Renato Gonik
    Pediatric Neurology, University of Florida College of Medicine, Gainesville, FL, USA.
  • Panayiotis V Benos
    Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA.
  • Seunghee Cha
    Center for Orphaned Autoimmune Disorders, University of Florida College of Dentistry, Gainesville, FL, USA; Oral Medicine, Oral and Maxillofacial Diagnostic Sciences, University of Florida College of Dentistry, Gainesville, FL, USA. Electronic address: scha@dental.ufl.edu.

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