Application of machine learning in assessing disease activity in SLE.

Journal: Lupus science & medicine
PMID: 40204296

Abstract

OBJECTIVE: SLE is a chronic autoimmune disease with immune complex deposition in various organs, causing inflammation. The Systemic Lupus Erythematosus Disease Activity Index 2000 assesses disease severity but is subjective. This study aimed to construct a machine learning model based on objective laboratory indicators to assess SLE disease activity.

Authors

  • Yun Wang
    Department of Anesthesiology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, People's Republic of China.
  • Peihong Yuan
    Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Wei Wei
    Dept. Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA.
  • Rujia Chen
    Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Ting Wang
    CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
  • Renren Ouyang
    Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Feng Wang
    Department of Oncology, Binzhou Medical University Hospital, Binzhou, Shandong, China.
  • Hongyan Hou
    Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. tjhouhongyan@tjh.tjmu.edu.cn.
  • Shiji Wu
    Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.

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