AIMC Topic: Diabetes Mellitus, Type 2
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Machine learning as new promising technique for selection of significant features in obese women with type 2 diabetes.
Hormone molecular biology and clinical investigation
Jan 11, 2020
Background The global trend of obesity and diabetes is considerable. Recently, the early diagnosis and accurate prediction of type 2 diabetes mellitus (T2DM) patients have been planned to be estimated according to precise and reliable methods, artifi...
Single-cell ATAC-Seq in human pancreatic islets and deep learning upscaling of rare cells reveals cell-specific type 2 diabetes regulatory signatures.
Molecular metabolism
Dec 20, 2019
OBJECTIVE: Type 2 diabetes (T2D) is a complex disease characterized by pancreatic islet dysfunction, insulin resistance, and disruption of blood glucose levels. Genome-wide association studies (GWAS) have identified > 400 independent signals that enc...
Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test.
PloS one
Dec 11, 2019
Diabetes is a large healthcare burden worldwide. There is substantial evidence that lifestyle modifications and drug intervention can prevent diabetes, therefore, an early identification of high risk individuals is important to design targeted preven...
Identification of repurposable drugs with beneficial effects on glucose control in type 2 diabetes using machine learning.
Pharmacology research & perspectives
Nov 20, 2019
Despite effective medications, rates of uncontrolled glucose levels in type 2 diabetes remain high. We aimed to test the utility of machine learning applied to big data in identifying the potential role of concomitant drugs not taken for diabetes whi...
Application of machine learning methodology to assess the performance of DIABETIMSS program for patients with type 2 diabetes in family medicine clinics in Mexico.
BMC medical informatics and decision making
Nov 12, 2019
BACKGROUND: The study aimed to assess the performance of a multidisciplinary-team diabetes care program called DIABETIMSS on glycemic control of type 2 diabetes (T2D) patients, by using available observational patient data and machine-learning-based ...
Development of a Deep Learning Model for Dynamic Forecasting of Blood Glucose Level for Type 2 Diabetes Mellitus: Secondary Analysis of a Randomized Controlled Trial.
JMIR mHealth and uHealth
Nov 1, 2019
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a major public health burden. Self-management of diabetes including maintaining a healthy lifestyle is essential for glycemic control and to prevent diabetes complications. Mobile-based health data can p...
Predicting short- and long-term glycated haemoglobin response after insulin initiation in patients with type 2 diabetes mellitus using machine-learning algorithms.
Diabetes, obesity & metabolism
Sep 30, 2019
AIM: To assess the potential of supervised machine-learning techniques to identify clinical variables for predicting short-term and long-term glycated haemoglobin (HbA1c) response after insulin treatment initiation in patients with type 2 diabetes me...
Building Risk Prediction Models for Type 2 Diabetes Using Machine Learning Techniques.
Preventing chronic disease
Sep 19, 2019
INTRODUCTION: As one of the most prevalent chronic diseases in the United States, diabetes, especially type 2 diabetes, affects the health of millions of people and puts an enormous financial burden on the US economy. We aimed to develop predictive m...
Machine Learning to Predict the Risk of Incident Heart Failure Hospitalization Among Patients With Diabetes: The WATCH-DM Risk Score.
Diabetes care
Sep 13, 2019
OBJECTIVE: To develop and validate a novel, machine learning-derived model to predict the risk of heart failure (HF) among patients with type 2 diabetes mellitus (T2DM).
Predicting the onset of type 2 diabetes using wide and deep learning with electronic health records.
Computer methods and programs in biomedicine
Aug 27, 2019
OBJECTIVE: Diabetes is responsible for considerable morbidity, healthcare utilisation and mortality in both developed and developing countries. Currently, methods of treating diabetes are inadequate and costly so prevention becomes an important step ...
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