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Diabetes Mellitus, Type 2

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Carotid Intima-Media Thickness and Visit-to-Visit HbA1c Variability Predict Progression of Chronic Kidney Disease in Type 2 Diabetic Patients with Preserved Kidney Function.

Journal of diabetes research
. Subclinical atherosclerosis and long-term glycemic variability have been reported to predict incident chronic kidney disease (CKD) in the general population. However, these associations have not been investigated in patients with type 2 diabetes wi...

Development of Type 2 Diabetes Mellitus Phenotyping Framework Using Expert Knowledge and Machine Learning Approach.

Journal of diabetes science and technology
BACKGROUND: Phenotyping is an automated technique that can be used to distinguish patients based on electronic health records. To improve the quality of medical care and advance type 2 diabetes mellitus (T2DM) research, the demand for T2DM phenotypin...

An Intelligible Risk Stratification Model Based on Pairwise and Size Constrained Kmeans.

IEEE journal of biomedical and health informatics
Having a system to stratify individuals according to risk is key to clinical disease prevention. This allows individuals identified at different risk tiers to benefit from further investigation and intervention. But the same risk score estimated for ...

Predictors of in-hospital mortality following major lower extremity amputations in type 2 diabetic patients using artificial neural networks.

BMC medical research methodology
BACKGROUND: Outcome prediction is important in the clinical decision-making process. Artificial neural networks (ANN) have been used to predict the risk of post-operative events, including survival, and are increasingly being used in complex medical ...

Prediction of Incident Diabetes in the Jackson Heart Study Using High-Dimensional Machine Learning.

PloS one
Statistical models to predict incident diabetes are often based on limited variables. Here we pursued two main goals: 1) investigate the relative performance of a machine learning method such as Random Forests (RF) for detecting incident diabetes in ...

A machine learning-based framework to identify type 2 diabetes through electronic health records.

International journal of medical informatics
OBJECTIVE: To discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide association study (PheWAS), more cases (T2DM subjects) and controls (subjects wit...

Temporal changes in plasma markers of oxidative stress following laparoscopic sleeve gastrectomy in subjects with impaired glucose regulation.

Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery
BACKGROUND: Laparoscopic sleeve gastrectomy (LSG) is an effective treatment for obesity and associated metabolic complications. Obesity and type 2 diabetes are associated with increased oxidative stress. Previous studies have examined changes in plas...

Diet-induced weight loss and markers of endothelial dysfunction and inflammation in treated patients with type 2 diabetes.

Clinical nutrition ESPEN
BACKGROUND & AIMS: Overweight and obesity increase cardiovascular mortality in patients with type 2 diabetes (T2D). In a recent trial, however, diet-induced weight loss did not reduce the cardiovascular risk of patients with T2D, possibly due to the ...

Learning statistical models of phenotypes using noisy labeled training data.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Traditionally, patient groups with a phenotype are selected through rule-based definitions whose creation and validation are time-consuming. Machine learning approaches to electronic phenotyping are limited by the paucity of labeled traini...