AIMC Topic: Blood Glucose
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Computational modelling for risk assessment of neurological disorder in diabetes using Hodgkin-Huxley model.
Computer methods and programs in biomedicine
Apr 20, 2025
BACKGROUND: Diabetes mellitus, characterized by chronic glucose dysregulation, significantly increases the risk of neurological disorders such as cognitive decline, seizures, and Alzheimer's disease. As neurons depend on glucose for energy, fluctuati...
Diabetes: Non-Invasive Blood Glucose Monitoring Using Federated Learning with Biosensor Signals.
Biosensors
Apr 16, 2025
Diabetes is a growing global health concern, affecting millions and leading to severe complications if not properly managed. The primary challenge in diabetes management is maintaining blood glucose levels (BGLs) within a safe range to prevent compli...
Estimated glucose disposal rate outperforms other insulin resistance surrogates in predicting incident cardiovascular diseases in cardiovascular-kidney-metabolic syndrome stages 0-3 and the development of a machine learning prediction model: a nationwide prospective cohort study.
Cardiovascular diabetology
Apr 16, 2025
BACKGROUND: The American Heart Association recently introduced the concept of cardiovascular-kidney-metabolic (CKM) syndrome, highlighting the increasing importance of the complex interplay between metabolic, renal, and cardiovascular diseases (CVD)....
Incidence
Time Factors
Insulin Resistance
Longitudinal Studies
Middle Aged
Risk Assessment
China
Blood Glucose
Metabolic Syndrome
Kidney Diseases
Predictive Value of Tests
Decision Support Techniques
Prospective Studies
Biomarkers
Prognosis
Aged
Male
Cardiovascular Diseases
Female
Risk Factors
Humans
Machine Learning
A deep learning approach for blood glucose monitoring and hypoglycemia prediction in glycogen storage disease.
Scientific reports
Apr 15, 2025
Glycogen storage disease (GSD) is a group of rare inherited metabolic disorders characterized by abnormal glycogen storage and breakdown. These disorders are caused by mutations in G6PC1, which is essential for proper glucose storage and metabolism. ...
Predicting diabetes mellitus metabolic goals and chronic complications transitions-analysis based on natural language processing and machine learning models.
PloS one
Apr 15, 2025
OBJECTIVE: To estimate Diabetes mellitus (DM) progression at one and two years in terms of glycemic targets and development of complications.
Personalized glucose forecasting for people with type 1 diabetes using large language models.
Computer methods and programs in biomedicine
Apr 2, 2025
BACKGROUND AND OBJECTIVE: Type 1 Diabetes (T1D) is an autoimmune disease that requires exogenous insulin via Multiple Daily Injections (MDIs) or subcutaneous pumps to maintain targeted glucose levels. Despite the advances in Continuous Glucose Monito...
Effectiveness of a community intervention program on healthy lifestyles (PREDICOL) among adults with prediabetes in two Latin American cities: A quasi-experimental study.
Primary care diabetes
Mar 29, 2025
PURPOSE: This study aimed to measure the impact of a community-based lifestyle modification intervention program on the Health-Related Quality of Life (HRQoL) of adults with prediabetes in two Latin American cities.
Which approach better predicts diabetes: Traditional econometric methods or machine learning? Evidence from a cross-sectional study in South Korea.
Computers in biology and medicine
Mar 23, 2025
To prevent chronic disease from getting worse, it is important to detect and predict it at an early stage. Therefore, the accuracy of the prediction is particularly important. To investigate the accuracy of different methods, this study compares the ...
Personalized Blood Glucose Forecasting From Limited CGM Data Using Incrementally Retrained LSTM.
IEEE transactions on bio-medical engineering
Mar 21, 2025
For people with Type 1 diabetes (T1D), accurate blood glucose (BG) forecasting is crucial for the effective delivery of insulin by Artificial Pancreas (AP) systems. Deep learning frameworks like Long Short-Term-Memory (LSTM) have been widely used to ...
Surrogate markers of insulin resistance and coronary artery disease in type 2 diabetes: U-shaped TyG association and insights from machine learning integration.
Lipids in health and disease
Mar 15, 2025
BACKGROUND: Surrogate insulin resistance (IR) indices are simpler and more practical alternatives to insulin-based IR indicators for clinical use. This study explored the association between surrogate IR indices, including triglyceride-glucose index ...
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