This paper is in the following e-collection/theme issue:

Machine Learning (1465) Clinical Information and Decision Making (1407) New Methods (944) Public (e)Health, Digital Epidemiology and Public Health Informatics (725) Research Instruments, Questionnaires, and Tools (576) Decision Support for Health Professionals (1185) Tools, Programs and Algorithms (266) Artificial Intelligence in Diabetes Care and Prevention (29) Diabetes Prevention (83)

Published on in Vol 8, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16850, first published .
Predicting the Development of Type 2 Diabetes in a Large Australian Cohort Using Machine-Learning Techniques: Longitudinal Survey Study

Predicting the Development of Type 2 Diabetes in a Large Australian Cohort Using Machine-Learning Techniques: Longitudinal Survey Study

Predicting the Development of Type 2 Diabetes in a Large Australian Cohort Using Machine-Learning Techniques: Longitudinal Survey Study

Authors of this article:

Lei Zhang1 Author Orcid Image ;   Xianwen Shang2 Author Orcid Image ;   Subhashaan Sreedharan2 Author Orcid Image ;   Xixi Yan2 Author Orcid Image ;   Jianbin Liu2 Author Orcid Image ;   Stuart Keel2 Author Orcid Image ;   Jinrong Wu2 Author Orcid Image ;   Wei Peng3 Author Orcid Image ;   Mingguang He2 Author Orcid Image
Article Authors Cited by (23) Tweetations (2) Metrics
All Time | Last Month | Last Six Months | Last Year
There are currently no tweets available for this article within the specified range.