Machine learning for predicting diabetes risk in western China adults.

ABSTRACT:

Objective

Diabetes mellitus is a global epidemic disease. Long-time exposure of patients to hyperglycemia can lead to various type of chronic tissue damage. Early diagnosis of and screening for diabetes are crucial to population health.

Methods

We collected the national physical examination data in Xinjiang, China, in 2020 (a total of more than 4 million people). Three types of physical examination indices were analyzed: questionnaire, routine physical examination and laboratory values. Integrated learning, deep learning and logistic regression methods were used to establish a risk model for type-2 diabetes mellitus. In addition, to improve the convenience and flexibility of the model, a diabetes risk score card was established based on logistic regression to assess the risk

SUBMITTER: Li L 

PROVIDER: S-EPMC10373320 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature