Development of an immunoinflammatory indicator-related dynamic nomogram based on machine learning for the prediction of intravenous immunoglobulin-resistant Kawasaki disease patients.

Abstract

Authors

• Yue Wang
  Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
• Yinyin Cao
  Cardiovascular Center, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China. Electronic address: yinyin19881126@126.com.
• Yang Li
  Occupation of Chinese Center for Disease Control and Prevention, Beijing, China.
• Fenhua Zhu
  Clinical Laboratory Center, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China. Electronic address: gzffdek399@sina.com.
• Meifen Yuan
  Clinical Laboratory Center, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China. Electronic address: ymf19881126@126.com.
• Jin Xu
  Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, and School of Statistics, East China Normal University, Shanghai, China.
• Xiaojing Ma
  Robert F. Smith School of Chemical & Biomolecular Engineering, Cornell University, Ithaca, NY 14850, USA.
• Jian Li
  Fujian Key Laboratory of Traditional Chinese Veterinary Medicine and Animal Health, College of Animal Science, Fujian Agriculture and Forestry University, Fuzhou, China.

Keywords

External Resources