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

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).

Methods

A total of 4723 patients were included in the analysis (4430 with T2DM and 293 with DPN). TFDA-1 was used to obtain tongue images during a questionnaire survey. LASSO (least absolute shrinkage and selection operator) logistic regression model wi

SUBMITTER: Tian Z 

PROVIDER: S-EPMC11837659 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature