Study on risk factors of diabetic peripheral neuropathy and establishment of a prediction model by machine learning.

ABSTRACT:

Background

Diabetic peripheral neuropathy (DPN) is a common complication of diabetes. Predicting the risk of developing DPN is important for clinical decision-making and designing clinical trials.

Methods

We retrospectively reviewed the data of 1278 patients with diabetes treated in two central hospitals from 2020 to 2022. The data included medical history, physical examination, and biochemical index test results. After feature selection and data balancing, the cohort was divided into training and internal validation datasets at a 7:3 ratio. Training was made in logistic regression, k-nearest neighbor, decision tree, naive bayes, random forest, and extreme gradient boosting (XGBoost) based on machine learning. The k-fold cross-validation was used for model assessment, and th

SUBMITTER: Lian X 

PROVIDER: S-EPMC10394817 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature