Diabetic peripheral neuropathy detection of type 2 diabetes using machine learning from TCM features: a cross-sectional study
This cross-sectional study demonstrates that the RF and LGBM models can screen for high-risk DPN in T2DM patients using TCM symptoms and tongue features. The identified key TCM-related features, such as age, tongue coating, and other symptoms, may be advantageous in developing preventative measures for T2DM patients.
Authors
- Dongjun Wang (ORCID: https://orcid.org/0000-0002-4206-9626)
- Yadong Fan
- Xuan Sun (ORCID: https://orcid.org/0000-0001-8831-6525)
- Zhikui Tian
- Xiaofei Liu (ORCID: https://orcid.org/0000-0002-1968-3644)
- Hongwu Wang (ORCID: https://orcid.org/0000-0002-1058-245X)
- JiZhong Zhang
- Gao Lu
Institutions
- Tianjin University of Traditional Chinese Medicine (CN)
- Binzhou Medical University (CN)
- North China University of Science and Technology (CN)
- Qilu University of Technology (CN)
- Qilu Hospital of Shandong University (CN)
- Yangzhou University (CN)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2025-02-18
- DOI
- https://doi.org/10.1186/s12911-025-02932-w
- Citations
- 5
- Primary Topic
- Diabetic Foot Ulcer Assessment and Management
- Type
- article
- Field-Weighted Citation Impact
- 6.47
Funders
- Natural Science Foundation of Hebei Province
- National Key Research and Development Program of China