Comparative study on risk prediction model of type 2 diabetes based on machine learning theory: a cross-sectional study.

ABSTRACT:

Objectives

To compare the prediction effects of six models based on machine learning theories, which can provide a methodological reference for predicting the risk of type 2 diabetes mellitus (T2DM).

Setting and participants

This study was based on the monitoring data of chronic disease risk factors in Dongguan residents from 2016 to 2018. The multistage cluster random sampling method was adopted at each monitoring site, and 4157 people were finally selected. In the initial population, we excluded individuals with more than 20% missing data and eventually included 4106 subjects.

Design

K nearest neighbour algorithm and synthetic minority oversampling technique were used to process the data. Single factor analysis was used for preliminary selection of variables. The 10

SUBMITTER: Wang S 

PROVIDER: S-EPMC10465890 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature