AIMC Topic: Blood Glucose Self-Monitoring

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Generation of Individualized Synthetic Data for Augmentation of the Type 1 Diabetes Data Sets Using Deep Learning Models.

Sensors (Basel, Switzerland) Jun 30, 2022
In this paper, we present a methodology based on generative adversarial network architecture to generate synthetic data sets with the intention of augmenting continuous glucose monitor data from individual patients. We use these synthetic data with t...
Neural Networks, Computer Computer Simulation Deep Learning Humans Hypoglycemia Blood Glucose Blood Glucose Self-Monitoring Cohort Studies Datasets as Topic Diabetes Mellitus, Type 1
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Optimization and Evaluation of an Intelligent Short-Term Blood Glucose Prediction Model Based on Noninvasive Monitoring and Deep Learning Techniques.

Journal of healthcare engineering Apr 11, 2022
Continuous noninvasive blood glucose monitoring and estimation management by using photoplethysmography (PPG) technology always have a series of problems, such as substantial time variability, inaccuracy, and complex nonlinearity. This paper proposes...
Neural Networks, Computer Humans Blood Glucose Algorithms Blood Glucose Self-Monitoring Deep Learning
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A Novel Extra Tree Ensemble Optimized DL Framework (ETEODL) for Early Detection of Diabetes.

Frontiers in public health Feb 15, 2022
Diabetes has been recognized as a global medical problem for more than half a century. Patients with diabetes can benefit from the Internet of Things (IoT) devices such as continuous glucose monitoring (CGM), intelligent pens, and similar devices. Sm...
Algorithms Humans Blood Glucose Self-Monitoring Blood Glucose Machine Learning Diabetes Mellitus
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A machine learning-based on-demand sweat glucose reporting platform.

Scientific reports Feb 14, 2022
Diabetes is a chronic endocrine disease that occurs due to an imbalance in glucose levels and altering carbohydrate metabolism. It is a leading cause of morbidity, resulting in a reduced quality of life even in developed societies, primarily affected...
Young Adult Adult Adolescent Humans Biomarkers Biosensing Techniques Diabetes Mellitus Electrochemical Techniques Wearable Electronic Devices Blood Glucose Cohort Studies Eccrine Glands Blood Glucose Self-Monitoring Dielectric Spectroscopy Sweat Supervised Machine Learning Healthy Volunteers
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Non-invasively accuracy enhanced blood glucose sensor using shallow dense neural networks with NIR monitoring and medical features.

Scientific reports Feb 2, 2022
Non-invasive and accurate method for continuous blood glucose monitoring, the self-testing of blood glucose is in quest for better diagnosis, control and the management of diabetes mellitus (DM). Therefore, this study reports a multiple photonic band...
Blood Glucose Self-Monitoring Humans Spectroscopy, Near-Infrared Neural Networks, Computer Blood Glucose Biosensing Techniques
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A Deep Learning Framework for Automatic Meal Detection and Estimation in Artificial Pancreas Systems.

Sensors (Basel, Switzerland) Jan 8, 2022
Current artificial pancreas (AP) systems are hybrid closed-loop systems that require manual meal announcements to manage postprandial glucose control effectively. This poses a cognitive burden and challenge to users with T1D since this relies on freq...
Diabetes Mellitus, Type 1 Blood Glucose Self-Monitoring Meals Insulin Infusion Systems Pancreas, Artificial Deep Learning Humans Blood Glucose Insulin Algorithms Adult
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Multi-step ahead predictive model for blood glucose concentrations of type-1 diabetic patients.

Scientific reports Dec 21, 2021
Continuous monitoring of blood glucose (BG) levels is a key aspect of diabetes management. Patients with Type-1 diabetes (T1D) require an effective tool to monitor these levels in order to make appropriate decisions regarding insulin administration a...
Humans Neural Networks, Computer Algorithms Diabetes Mellitus, Type 1 Deep Learning Blood Glucose Self-Monitoring Blood Glucose
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Developing an Individual Glucose Prediction Model Using Recurrent Neural Network.

Sensors (Basel, Switzerland) Nov 12, 2020
In this study, we propose a personalized glucose prediction model using deep learning for hospitalized patients who experience Type-2 diabetes. We aim for our model to assist the medical personnel who check the blood glucose and control the amount of...
Glucose Blood Glucose Self-Monitoring Neural Networks, Computer Algorithms Blood Glucose Humans
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Multi-Hour Blood Glucose Prediction in Type 1 Diabetes: A Patient-Specific Approach Using Shallow Neural Network Models.

Diabetes technology & therapeutics Oct 13, 2020
Considering current insulin action profiles and the nature of glycemic responses to insulin, there is an acute need for longer term, accurate, blood glucose predictions to inform insulin dosing schedules and enable effective decision support for the...
Humans Blood Glucose Self-Monitoring Neural Networks, Computer Insulin Algorithms Diabetes Mellitus, Type 1 Blood Glucose Hypoglycemic Agents
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Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors.

Sensors (Basel, Switzerland) Jul 10, 2020
Wearable continuous glucose monitoring (CGM) sensors are revolutionizing the treatment of type 1 diabetes (T1D). These sensors provide in real-time, every 1-5 min, the current blood glucose concentration and its rate-of-change, two key pieces of info...
Disease Management Humans Insulin Infusion Systems Artificial Intelligence Wearable Electronic Devices Diabetes Mellitus, Type 1 Blood Glucose Blood Glucose Self-Monitoring
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