Forecasting Achievement of Inactive Disease in Juvenile Idiopathic Arthritis with Artificial Intelligence

Forecasting Achievement of Inactive Disease in Juvenile Idiopathic Arthritis with Artificial Intelligence

<b>Objective:</b> to seek for predictors of inactive disease (ID) in juvenile idiopathic arthritis (JIA) with artificial intelligence. <b>Methods:</b> The clinical charts of patients seen within 6 months after disease onset between 2007 and 2019 and with follow-up visits at 6...

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Bibliographic Details
Main Authors: Ana I. Rebollo-Giménez, Francesca Ridella, Silvia Maria Orsi, Elena Aldera, Marco Burrone, Valentina Natoli, Silvia Rosina, Alessandro Consolaro, Esperanza Naredo, Angelo Ravelli, Davide Cangelosi
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Children
Subjects:
juvenile idiopathic arthritis
pediatric rheumatology
outcome predictors
inactive disease
artificial intelligence
machine learning
Online Access:https://www.mdpi.com/2227-9067/12/6/741
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