Establishment and analysis of a novel diagnostic model for systemic juvenile idiopathic arthritis based on machine learning

Establishment and analysis of a novel diagnostic model for systemic juvenile idiopathic arthritis based on machine learning

Abstract Background Systemic juvenile idiopathic arthritis (SJIA) is a form of childhood arthritis with clinical features such as fever, lymphadenopathy, arthritis, rash, and serositis. It seriously affects the growth and development of children and has a high rate of disability and mortality. SJIA...

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Bibliographic Details
Main Authors: Pan Ding, Yi Du, Xinyue Jiang, Huajian Chen, Li Huang
Format: Article
Language:English
Published: BMC 2024-01-01
Series:Pediatric Rheumatology Online Journal
Subjects:
Systemic juvenile idiopathic arthritis
Machine learning
Random forest
GEO
Diagnostic model
Online Access:https://doi.org/10.1186/s12969-023-00949-x

Internet

https://doi.org/10.1186/s12969-023-00949-x

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