Machine learning in lymphocyte and immune biomarker analysis for childhood thyroid diseases in China.

Journal: BMC pediatrics
PMID: 40155866

Abstract

OBJECTIVE: This study aims to characterize and analyze the expression of representative biomarkers like lymphocytes and immune subsets in children with thyroid disorders. It also intends to develop and evaluate a machine learning model to predict if patients have thyroid disorders based on their clinical characteristics, ultimately providing insights to enhance the clinical guidelines for the pathogenesis of childhood thyroid disorders.

Authors

  • Ruizhe Yang
    State Key Laboratory of Robotics and System, Harbin Institute of Technology, West Da-zhi Street 92, Harbin, Heilongjiang 150001, People's Republic of China. rykhit@hit.edu.cn.
  • Wei Li
    Department of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Qing Niu
    School of Pediatrics, Nanjing Medical University, Nanjing, 211166, China.
  • Wentao Yang
    b Department of Hepatobiliary and Pancreatic Surgery , the Second Affiliated Hospital of Nanchang University , Nanchang , PR China.
  • Wei Gu
    Department of Ophthalmology, Beijing Aier Intech Eye Hospital, Beijing, China.
  • Xu Wang
    Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907.

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