Diabetic peripheral neuropathy detection of type 2 diabetes using machine learning from TCM features: a cross-sectional study.

Journal: BMC medical informatics and decision making
PMID: 39966886

Abstract

AIMS: Diabetic peripheral neuropathy (DPN) is the most common complication of diabetes mellitus. Early identification of individuals at high risk of DPN is essential for successful early intervention. Traditional Chinese medicine (TCM) tongue diagnosis, one of the four diagnostic methods, lacks specific algorithms for TCM symptoms and tongue features. This study aims to develop machine learning (ML) models based on TCM to predict the risk of diabetic peripheral neuropathy (DPN) in patients with type 2 diabetes mellitus (T2DM).

Authors

  • Zhikui Tian
    School of Rehabilitation Medicine, Qilu Medical University, Shandong, 255300, China.
  • JiZhong Zhang
    School of Rehabilitation Medicine, Qilu Medical University, Shandong, 255300, China.
  • Yadong Fan
    Medical College of Yangzhou University, YangZhou, 225000, China.
  • Xuan Sun
    State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, 430070, PR China.
  • Dongjun Wang
    College of Traditional Chinese Medicine, North China University of Science and Technology, Tangshan, 063000, China.
  • Xiaofei Liu
    Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China.
  • Guohui Lu
    Department of Neurosurgery, The First Affiliated Hospital of Nanchang University, Nanchang 330006, People's Republic of China. Electronic address: guohui-lu@163.com.
  • Hongwu Wang
    Respiratory Disease Center, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.

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