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

• Published in: BMJ open Vol. 13; no. 8; p. e069018
• Main Authors: Wang, Shu, Chen, Rong, Wang, Shuang, Kong, Danli, Cao, Rudai, Lin, Chunwen, Luo, Ling, Huang, Jialu, Zhang, Qiaoli, Yu, Haibing, Ding, Yuan Lin
• Format: Journal Article
• Language: English
• Published: London British Medical Journal Publishing Group 29.08.2023; BMJ Publishing Group LTD; BMJ Publishing Group
• Series: Original research
• Subjects: Accuracy; Artificial intelligence; Blood pressure; Cholesterol; Chronic illnesses; Cross-sectional studies; Decision trees; Diabetes; Disease; EPIDEMIOLOGY; General diabetes; Glucose; Machine learning; Neural networks; Patients; Public Health; Regression analysis; Risk factors; Sample size; STATISTICS & RESEARCH METHODS; Support vector machines; Variables

ObjectivesTo 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 participantsThis study was based on the monitoring data of chronic disease risk factors in...