AIMC Topic: Blood Glucose
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Machine Learning-Driven D-Glucose Prediction Using a Novel Biosensor for Non-Invasive Diabetes Management.
Biosensors
Mar 1, 2025
Developing reliable noninvasive diagnostic and monitoring systems for diabetes remains a significant challenge, especially in the e-healthcare domain, due to computational inefficiencies and limited predictive accuracy in current approaches. The curr...
Stress hyperglycemia ratio and machine learning model for prediction of all-cause mortality in patients undergoing cardiac surgery.
Cardiovascular diabetology
Feb 15, 2025
BACKGROUND: The stress hyperglycemia ratio (SHR) was developed to reduce the effects of long-term chronic glycemic factors on stress hyperglycemia levels, which was associated with adverse clinical outcomes. This study aims to evaluate the relationsh...
Humans
Machine Learning
Female
Risk Factors
Aged
Male
Decision Support Techniques
Databases, Factual
Biomarkers
Retrospective Studies
Cause of Death
Cardiac Surgical Procedures
Hospital Mortality
Stress, Physiological
Hyperglycemia
Middle Aged
Treatment Outcome
Risk Assessment
Predictive Value of Tests
Blood Glucose
Time Factors
Optimising test intervals for individuals with type 2 diabetes: A machine learning approach.
PloS one
Feb 13, 2025
BACKGROUND: Chronic disease monitoring programs often adopt a one-size-fits-all approach that does not consider variation in need, potentially leading to excessive or insufficient support for patients at different risk levels. Machine learning (ML) d...
Weight loss-independent changes in human growth hormone during water-only fasting: a secondary evaluation of a randomized controlled trial.
Frontiers in endocrinology
Feb 7, 2025
INTRODUCTION: Water-only fasting for one day or more may provide health benefits independent of weight loss. Human growth hormone (HGH) may play a key role in multiple fasting-triggered mechanisms. Whether HGH changes during fasting are independent o...
GARNN: An interpretable graph attentive recurrent neural network for predicting blood glucose levels via multivariate time series.
Neural networks : the official journal of the International Neural Network Society
Feb 5, 2025
Accurate prediction of future blood glucose (BG) levels can effectively improve BG management for people living with type 1 or 2 diabetes, thereby reducing complications and improving quality of life. The state of the art of BG prediction has been ac...
Estimation of Hematocrit Volume Using Blood Glucose Concentration through Extreme Gradient Boosting Regressor Machine Learning Model.
Journal of chemical information and modeling
Feb 5, 2025
Lifestyle diseases such as cardiovascular disorders, diabetes, etc. affect the physiological metabolism and become chronic upon negligence. Diabetes is one of the key factors that is interlinked with a plethora of diseases. Health management can be a...
Prediction of insulin resistance using multiple adaptive regression spline in Chinese women.
Endocrine journal
Feb 1, 2025
Insulin resistance (IR) is the core for type 2 diabetes and metabolic syndrome. The homeostasis assessment model is a straightforward and practical tool for quantifying insulin resistance (HOMA-IR). Multiple adaptive regression spline (MARS) is a mac...
Optimizing hypoglycaemia prediction in type 1 diabetes with Ensemble Machine Learning modeling.
BMC medical informatics and decision making
Jan 31, 2025
BACKGROUND: Type 1 diabetes (T1D) is a chronic endocrine disorder characterized by high blood glucose levels, impacting millions of people globally. Its management requires intensive insulin therapy, frequent blood glucose monitoring, and lifestyle a...
The triglyceride-glucose index and its obesity-related derivatives as predictors of all-cause and cardiovascular mortality in hypertensive patients: insights from NHANES data with machine learning analysis.
Cardiovascular diabetology
Jan 29, 2025
BACKGROUND: Hypertension (HTN) is a global public health concern and a major risk factor for cardiovascular disease (CVD) and mortality. Insulin resistance (IR) plays a crucial role in HTN-related metabolic dysfunction, but its assessment remains cha...
A safe-enhanced fully closed-loop artificial pancreas controller based on deep reinforcement learning.
PloS one
Jan 27, 2025
Patients with type 1 diabetes and their physicians have long desired a fully closed-loop artificial pancreas (AP) system that can alleviate the burden of blood glucose regulation. Although deep reinforcement learning (DRL) methods theoretically enabl...
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