Early Prediction of Clinical Response to Etanercept Treatment in Juvenile Idiopathic Arthritis Using Machine Learning

• Hlavní autoři: Xiaolan Mo (Autor), Xiujuan Chen (Autor), Chifong Ieong (Autor), Song Zhang (Autor), Huiyi Li (Autor), Jiali Li (Autor), Guohao Lin (Autor), Guangchao Sun (Autor), Fan He (Autor), Yanling He (Autor), Ying Xie (Autor), Ping Zeng (Autor), Yilu Chen (Autor), Huiying Liang (Autor), Huasong Zeng (Autor)
• Médium: Kniha
• Vydáno: Frontiers Media S.A., 2020-07-01T00:00:00Z.
• Témata: article
• On-line přístup: Connect to this object online.

Background and AimsAt present, there is a lack of simple and reliable model for early prediction of the efficacy of etanercept in the treatment of juvenile idiopathic arthritis (JIA). This study aimed to generate and validate prediction models of etanercept efficacy in patients with JIA before admin...