AIMC Topic: Blood Glucose

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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...
Humans Forecasting Female Pilot Projects Blood Glucose Self-Management Diabetes Mellitus, Type 2 Male Predictive Value of Tests Middle Aged Deep Learning
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Utility of Big Data in Predicting Short-Term Blood Glucose Levels in Type 1 Diabetes Mellitus Through Machine Learning Techniques.

Sensors (Basel, Switzerland) Oct 16, 2019
Machine learning techniques combined with wearable electronics can deliver accurate short-term blood glucose level prediction models. These models can learn personalized glucose-insulin dynamics based on the sensor data collected by monitoring severa...
Diabetes Mellitus, Type 1 Humans Machine Learning Middle Aged Female Big Data Adolescent Blood Glucose Young Adult Adult Male
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Predicting Quality of Overnight Glycaemic Control in Type 1 Diabetes Using Binary Classifiers.

IEEE journal of biomedical and health informatics Sep 13, 2019
In type 1 diabetes management, maintaining nocturnal blood glucose within target range can be challenging. Although semi-automatic systems to modulate insulin pump delivery, such as low-glucose insulin suspension and the artificial pancreas, are star...
Humans Sleep Glycemic Control Blood Glucose Insulin Machine Learning Decision Support Systems, Clinical Algorithms Diabetes Mellitus, Type 1 Adult Middle Aged
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Prediction of metabolic status of dairy cows in early lactation with on-farm cow data and machine learning algorithms.

Journal of dairy science Aug 30, 2019
Metabolic status of dairy cows in early lactation can be evaluated using the concentrations of plasma β-hydroxybutyrate (BHB), free fatty acids (FFA), glucose, insulin, and insulin-like growth factor 1 (IGF-1). These plasma metabolites and metabolic ...
Energy Metabolism Milk Fatty Acids, Nonesterified 3-Hydroxybutyric Acid Insulin Cattle Body Weight Lactation Animals Farms Blood Glucose Machine Learning Algorithms Pregnancy Female Parity
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The parameter Houlihan: A solution to high-throughput identifiability indeterminacy for brutally ill-posed problems.

Mathematical biosciences Aug 24, 2019
One way to interject knowledge into clinically impactful forecasting is to use data assimilation, a nonlinear regression that projects data onto a mechanistic physiologic model, instead of a set of functions, such as neural networks. Such regressions...
Models, Biological Blood Glucose Insulin Diabetes Mellitus, Type 2 Models, Statistical Humans Machine Learning Adult Middle Aged
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Hyper-G: An Artificial Intelligence Tool for Optimal Decision-Making and Management of Blood Glucose Levels in Surgery Patients.

Methods of information in medicine Aug 9, 2019
BACKGROUND: Hyperglycemia or high blood glucose during surgery is associated with poor postoperative outcome. Knowing in advance which patients may develop hyperglycemia allows optimal assignment of resources and earlier initiation of glucose managem...
Humans Artificial Intelligence Data Analysis Models, Theoretical Decision Making Surgical Procedures, Operative Female Male User-Computer Interface Blood Glucose
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GluNet: A Deep Learning Framework for Accurate Glucose Forecasting.

IEEE journal of biomedical and health informatics Jul 29, 2019
For people with Type 1 diabetes (T1D), forecasting of blood glucose (BG) can be used to effectively avoid hyperglycemia, hypoglycemia and associated complications. The latest continuous glucose monitoring (CGM) technology allows people to observe glu...
Humans Algorithms Deep Learning Blood Glucose Diabetes Mellitus, Type 1 Probability Blood Glucose Self-Monitoring
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Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes.

Artificial intelligence in medicine Jul 26, 2019
BACKGROUND: Diabetes mellitus (DM) is a metabolic disorder that causes abnormal blood glucose (BG) regulation that might result in short and long-term health complications and even death if not properly managed. Currently, there is no cure for diabet...
Patient-Specific Modeling Models, Biological Data Mining Blood Glucose Self-Monitoring Feeding Behavior Stress, Psychological Mobile Applications Humans Wearable Electronic Devices Diabetes Mellitus, Type 1 Machine Learning Hypoglycemic Agents Blood Glucose Diet Insulin Exercise
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TyG-er: An ensemble Regression Forest approach for identification of clinical factors related to insulin resistance condition using Electronic Health Records.

Computers in biology and medicine Jul 17, 2019
BACKGROUND: Insulin resistance is an early-stage deterioration of Type 2 diabetes. Identification and quantification of insulin resistance requires specific blood tests; however, the triglyceride-glucose (TyG) index can provide a surrogate assessment...
Diabetes Mellitus, Type 2 Insulin Resistance Triglycerides Aged Male Middle Aged Humans Blood Glucose Machine Learning Electronic Health Records Female
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Minimizing postprandial hypoglycemia in Type 1 diabetes patients using multiple insulin injections and capillary blood glucose self-monitoring with machine learning techniques.

Computer methods and programs in biomedicine Jun 27, 2019
BACKGROUND: Diabetic patients treated with intensive insulin therapies require a tight glycemic control and may benefit from advanced tools to predict blood glucose (BG) concentration levels and hypo/hyperglycemia events. Prediction systems using mac...
Adult Bayes Theorem Computer Simulation Blood Glucose Hypoglycemia False Positive Reactions Retrospective Studies Humans Sensitivity and Specificity Normal Distribution Insulin Postprandial Period Machine Learning Female Male Insulin Infusion Systems Diabetes Mellitus, Type 1 Algorithms Blood Glucose Self-Monitoring Reproducibility of Results Middle Aged Capillaries Hypoglycemic Agents
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