AIMC Topic: Blood Glucose

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Implementation of five machine learning methods to predict the 52-week blood glucose level in patients with type 2 diabetes.

Frontiers in endocrinology Jan 20, 2023
OBJECTIVE: For the patients who are suffering from type 2 diabetes, blood glucose level could be affected by multiple factors. An accurate estimation of the trajectory of blood glucose is crucial in clinical decision making. Frequent glucose measurem...
Humans Blood Glucose Hypoglycemic Agents Machine Learning Diabetes Mellitus, Type 2 Glycated Hemoglobin
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Estimation of a Machine Learning-Based Decision Rule to Reduce Hypoglycemia Among Older Adults With Type 1 Diabetes: A Post Hoc Analysis of Continuous Glucose Monitoring in the WISDM Study.

Journal of diabetes science and technology Jan 11, 2023
BACKGROUND: The Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) study demonstrated continuous glucose monitoring (CGM) reduced hypoglycemia over 6 months among older adults with type 1 diabetes (T1D) compared with blood glucose monitor...
Middle Aged Humans Blood Glucose Female Machine Learning Aged, 80 and over Aged Diabetes Mellitus, Type 1 Hypoglycemic Agents Clinical Decision Rules Male Blood Glucose Self-Monitoring Hypoglycemia Continuous Glucose Monitoring
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Personalized Blood Glucose Prediction for Type 1 Diabetes Using Evidential Deep Learning and Meta-Learning.

IEEE transactions on bio-medical engineering Dec 26, 2022
The availability of large amounts of data from continuous glucose monitoring (CGM), together with the latest advances in deep learning techniques, have opened the door to a new paradigm of algorithm design for personalized blood glucose (BG) predicti...
Diabetes Mellitus, Type 1 Humans Deep Learning Blood Glucose
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Time for Using Machine Learning for Dose Guidance in Titration of People With Type 2 Diabetes? A Systematic Review of Basal Insulin Dose Guidance.

Journal of diabetes science and technology Dec 23, 2022
BACKGROUND: Real-world studies of people with type 2 diabetes (T2D) have shown insufficient dose adjustment during basal insulin titration in clinical practice leading to suboptimal treatment. Thus, 60% of people with T2D treated with insulin do not ...
Insulin Diabetes Mellitus, Type 2 Hypoglycemic Agents Machine Learning Blood Glucose Humans
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Quantitative measurement of blood glucose influenced by multiple factors via photoacoustic technique combined with optimized wavelet neural networks.

Journal of biophotonics Dec 7, 2022
In this work, the photoacoustic (PA) quantitative measurement of blood glucose concentration (BGC) influenced by multiple factors was firstly investigated. A set of PA detection system of blood glucose considering the comprehensive influence of five ...
Animals Blood Glucose Rabbits Neural Networks, Computer Algorithms Nonlinear Dynamics Photoacoustic Techniques
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Leveraging IoT-Aware Technologies and AI Techniques for Real-Time Critical Healthcare Applications.

Sensors (Basel, Switzerland) Oct 10, 2022
Personalised healthcare has seen significant improvements due to the introduction of health monitoring technologies that allow wearable devices to unintrusively monitor physiological parameters such as heart health, blood pressure, sleep patterns, an...
Technology Aged Biocompatible Materials Blood Glucose Artificial Intelligence Delivery of Health Care Humans
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A Prediction Algorithm for Hypoglycemia Based on Support Vector Machine Using Glucose Level and Electrocardiogram.

Journal of medical systems Sep 14, 2022
A prediction algorithm for hypoglycemic events is proposed using glucose levels and electrocardiogram (ECG) with support vector machine (SVM). We extracted the corrected QT interval and five heart rate variability parameters from the ECG, along with ...
Blood Glucose Self-Monitoring Blood Glucose Electrocardiography Support Vector Machine Hypoglycemia Hypoglycemic Agents Humans Algorithms
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Deep learning fuzzy immersion and invariance control for type-I diabetes.

Computers in biology and medicine Aug 17, 2022
In this study, a novel approach is proposed for glucose regulation in type-I diabetes patients. Unlike most studies, the glucose-insulin metabolism is considered to be uncertain. A new approach on the basis of the Immersion and Invariance (I&I) theor...
Algorithms Computer Simulation Blood Glucose Insulin Deep Learning Humans Immersion Diabetes Mellitus, Type 1 Fuzzy Logic
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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...
Datasets as Topic Hypoglycemia Humans Blood Glucose Self-Monitoring Neural Networks, Computer Blood Glucose Computer Simulation Cohort Studies Deep Learning Diabetes Mellitus, Type 1
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Deduction learning for precise noninvasive measurements of blood glucose with a dozen rounds of data for model training.

Scientific reports Apr 20, 2022
Personalized modeling has long been anticipated to approach precise noninvasive blood glucose measurements, but challenged by limited data for training personal model and its unavoidable outlier predictions. To overcome these long-standing problems, ...
Photoplethysmography Neural Networks, Computer Deep Learning Algorithms Humans Blood Glucose
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