AIMC Topic: Blood Glucose

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Exploring the prognostic impact of triglyceride-glucose index in critically ill patients with first-ever stroke: insights from traditional methods and machine learning-based mortality prediction.

Cardiovascular diabetology Dec 18, 2024
BACKGROUND: The incidence and mortality of first-ever strokes have risen sharply, especially in the intensive care unit (ICU). Emerging surrogate for insulin resistance, triglyceride-glucose index (TyG), has been linked to stroke prognosis. We aims t...
Male Middle Aged Risk Assessment China Reproducibility of Results Databases, Factual Risk Factors Aged Biomarkers Predictive Value of Tests Prognosis Cause of Death Retrospective Studies Stroke Critical Illness Length of Stay Triglycerides Intensive Care Units Blood Glucose Female Time Factors Hospital Mortality Humans Machine Learning
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Modeling the fasting blood glucose response to basal insulin adjustment in type 2 diabetes: An explainable machine learning approach on real-world data.

International journal of medical informatics Dec 9, 2024
INTRODUCTION: Optimal basal insulin titration for people with type 2 diabetes is vital to effectively reducing the risk of complications. However, a sizeable proportion of people (30-50 %) remain in suboptimal glycemic control six months post-initiat...
Female Aged Male Middle Aged Humans Machine Learning Diabetes Mellitus, Type 2 Fasting Hypoglycemic Agents Blood Glucose Insulin
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Classification of glucose-level in deionized water using machine learning models and data pre-processing technique.

PloS one Dec 5, 2024
Accurate monitoring of glucose levels is essential in the field of diabetes detection and prevention to ensure appropriate treatment planning. Conventional blood glucose monitoring methods, although widely used, are intrusive and frequently result in...
Blood Glucose Water Spectrum Analysis, Raman Support Vector Machine Humans Glucose Machine Learning
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Hybrid CNN-GRU Model for Real-Time Blood Glucose Forecasting: Enhancing IoT-Based Diabetes Management with AI.

Sensors (Basel, Switzerland) Nov 30, 2024
For people with diabetes, controlling blood glucose level (BGL) is a significant issue since the disease affects how the body metabolizes food, which makes careful insulin regulation necessary. Patients have to manually check their blood sugar levels...
Deep Learning Blood Glucose Diabetes Mellitus, Type 1 Blood Glucose Self-Monitoring Humans Internet of Things Neural Networks, Computer Forecasting
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Prognostic value of glycaemic variability for mortality in critically ill atrial fibrillation patients and mortality prediction model using machine learning.

Cardiovascular diabetology Nov 26, 2024
BACKGROUND: The burden of atrial fibrillation (AF) in the intensive care unit (ICU) remains heavy. Glycaemic control is important in the AF management. Glycaemic variability (GV), an emerging marker of glycaemic control, is associated with unfavourab...
Retrospective Studies Critical Illness Intensive Care Units Female Reproducibility of Results Risk Factors Aged Decision Support Techniques Databases, Factual Biomarkers Predictive Value of Tests Risk Assessment Humans Prognosis Cause of Death Blood Glucose Machine Learning Atrial Fibrillation Aged, 80 and over Time Factors Glycemic Control Male Hospital Mortality Middle Aged
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Parental perspectives following the implementation of advanced hybrid closed-loop therapy in children and adolescents with type 1 diabetes and elevated glycaemia.

Diabetic medicine : a journal of the British Diabetic Association Nov 25, 2024
AIMS: To identify from a parental perspective facilitators and barriers of effective implementation of advanced hybrid closed-loop (AHCL) therapy in children and adolescents with type 1 diabetes (T1D) with elevated glycaemia.
Pancreas, Artificial Parents Adolescent Glycated Hemoglobin Humans Blood Glucose Self-Monitoring Blood Glucose Diabetes Mellitus, Type 1 Female Glycemic Control Insulin Hypoglycemic Agents Male Insulin Infusion Systems Child
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Robust diabetic prediction using ensemble machine learning models with synthetic minority over-sampling technique.

Scientific reports Nov 22, 2024
This paper addresses the pressing issue of diabetes, which is a widespread condition affecting a huge population worldwide. As cells become less responsive to insulin or fail to produce it adequately, blood sugar levels rise. This has the potential t...
Diabetes Mellitus Humans Machine Learning Algorithms Blood Glucose
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Shortcomings in the Evaluation of Blood Glucose Forecasting.

IEEE transactions on bio-medical engineering Nov 21, 2024
OBJECTIVE: Recent years have seen an increase in machine learning (ML)-based blood glucose (BG) forecasting models, with a growing emphasis on potential application to hybrid or closed-loop predictive glucose controllers. However, current approaches ...
Machine Learning Algorithms Forecasting Computer Simulation Humans Blood Glucose Blood Glucose Self-Monitoring
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AI-Based Noninvasive Blood Glucose Monitoring: Scoping Review.

Journal of medical Internet research Nov 19, 2024
BACKGROUND: Current blood glucose monitoring (BGM) methods are often invasive and require repetitive pricking of a finger to obtain blood samples, predisposing individuals to pain, discomfort, and infection. Noninvasive blood glucose monitoring (NIBG...
Blood Glucose Blood Glucose Self-Monitoring Humans Artificial Intelligence
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Convolutional neural network for colorimetric glucose detection using a smartphone and novel multilayer polyvinyl film microfluidic device.

Scientific reports Nov 17, 2024
Detecting glucose levels is crucial for diabetes patients as it enables timely and effective management, preventing complications and promoting overall health. In this endeavor, we have designed a novel, affordable point-of-care diagnostic device uti...
Polymethyl Methacrylate Lab-On-A-Chip Devices Deep Learning Blood Glucose Colorimetry Smartphone Glucose Humans Glucose Oxidase Neural Networks, Computer Polyvinyls
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