Establishment and health management application of a prediction model for high-risk complication combination of type 2 diabetes mellitus based on data mining.

ABSTRACT: In recent years, the prevalence of T2DM has been increasing annually, in particular, the personal and socioeconomic burden caused by multiple complications has become increasingly serious. This study aimed to screen out the high-risk complication combination of T2DM through various data mining methods, establish and evaluate a risk prediction model of the complication combination in patients with T2DM. Questionnaire surveys, physical examinations, and biochemical tests were conducted on 4,937 patients with T2DM, and 810 cases of sample data with complications were retained. The high-risk complication combination was screened by association rules based on the Apriori algorithm. Risk factors were screened using the LASSO regression model, random forest model, and support vector machine. A ri

SUBMITTER: Luo X 

PROVIDER: S-EPMC10409378 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature