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

Global Economic Burden of Diabetes in Adults: Projections From 2015 to 2030

(2018) Christian Bommer et al.   DIABETES CARE

IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045

(2018) N.H. Cho et al.   DIABETES RESEARCH AND CLINICAL PRACTICE

Big Data and Machine Learning in Health Care

(2018) Andrew L. Beam et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Effectiveness of the CANRISK tool in the identification of dysglycemia in First Nations and Métis in Canada

(2018) Gina Agarwal et al.   Health Promotion and Chronic Disease Prevention in Canada-Research Policy and Practice

Development and validation of QDiabetes-2018 risk prediction algorithm to estimate future risk of type 2 diabetes: cohort study

(2017) Julia Hippisley-Cox et al.   BMJ-British Medical Journal

Development and validation of QDiabetes-2018 risk prediction algorithm to estimate future risk of type 2 diabetes: cohort study

(2017) Julia Hippisley-Cox et al.   BMJ-British Medical Journal

Machine Learning and Data Mining Methods in Diabetes Research

(2017) Ioannis Kavakiotis et al.   Computational and Structural Biotechnology Journal

Burden of diabetes in Australia: life expectancy and disability-free life expectancy in adults with diabetes

(2016) Lili Huo et al.   DIABETOLOGIA

Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors

(2015) Narges Razavian et al.   Big Data

Screening for Prediabetes Using Machine Learning Models

(2014) Soo Beom Choi et al.   Computational and Mathematical Methods in Medicine

Development and Validation of a Patient Self-assessment Score for Diabetes Risk

(2013) Heejung Bang   ANNALS OF INTERNAL MEDICINE

Validating self-report of diabetes use by participants in the 45 and up study: a record linkage study

(2013) Elizabeth Jean Comino et al.   BMC HEALTH SERVICES RESEARCH

Non-invasive risk scores for prediction of type 2 diabetes (EPIC-InterAct): a validation of existing models

(2013) Andre Pascal Kengne et al.   Lancet Diabetes & Endocrinology

Gradient boosting machines, a tutorial

(2013) Alexey Natekin et al.   Frontiers in Neurorobotics

Comparison of three data mining models for predicting diabetes or prediabetes by risk factors

(2012) Xue-Hui Meng et al.   KAOHSIUNG JOURNAL OF MEDICAL SCIENCES

Changes in BMI, Duration of Overweight and Obesity, and Glucose Metabolism: 45 Years of Follow-up of a Birth Cohort

(2011) C. Power et al.   DIABETES CARE

The Leicester Risk Assessment score for detecting undiagnosed Type 2 diabetes and impaired glucose regulation for use in a multiethnic UK setting

(2010) L. J. Gray et al.   DIABETIC MEDICINE

A simple risk score identifies individuals at high risk of developing Type 2 diabetes: a prospective cohort study

(2008) M. Rahman et al.   FAMILY PRACTICE