AIMC Topic: Blood Glucose
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Dual smart sensor data-based deep learning network for premature infant hypoglycemia detection.
Scientific reports
Jul 2, 2025
In general, deficient birth weight neonates suffer from hypoglycemia, and this can be quite disadvantageous. Like oxygen, glucose is a building block of life and constitutes the significant share of energy produced by the fetus and the neonate during...
Detection of fasting blood sugar using a microwave sensor and convolutional neural network.
Scientific reports
Jul 2, 2025
Monitoring of fasting blood sugar (FBS) is a critical component in the diagnosis and management of diabetes, one of the most widespread chronic diseases globally. Microwave sensing-particularly through microstrip-based sensors-has recently gained att...
A supervised machine learning approach with feature selection for sex-specific biomarker prediction.
NPJ systems biology and applications
Jul 1, 2025
Biomarkers are crucial in aiding in disease diagnosis, prognosis, and treatment selection. Machine learning (ML) has emerged as an effective tool for identifying novel biomarkers and enhancing predictive modelling. However, sex-based bias in ML algor...
Research Gaps, Challenges, and Opportunities in Automated Insulin Delivery Systems.
Journal of diabetes science and technology
Jul 1, 2025
BACKGROUND: Since the discovery of the life-saving hormone insulin in 1921 by Dr Frederick Banting in 1921, there have been many critical discoveries and technical breakthroughs that have enabled people living with type 1 diabetes (T1D) to live longe...
Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sleeping times.
PloS one
Jun 25, 2025
Hypoglycemia is a major challenge for people with diabetes. Therefore, glycemic monitoring is an important aspect of diabetes management. However, current methods such as finger pricking and continuous glucose monitoring systems (CGMS) are invasive, ...
Global research trends in AI-assisted blood glucose management: a bibliometric study.
Frontiers in endocrinology
May 28, 2025
BACKGROUND: AI-assisted blood glucose management has become a promising method to enhance diabetes care, leveraging technologies like continuous glucose monitoring (CGM) and predictive models. A comprehensive bibliometric analysis is needed to unders...
Continuous glucose monitoring combined with artificial intelligence: redefining the pathway for prediabetes management.
Frontiers in endocrinology
May 26, 2025
Prediabetes represents an early stage of glucose metabolism disorder with significant public health implications. Although traditional lifestyle interventions have demonstrated some efficacy in preventing the progression to type 2 diabetes, their lim...
Development of Non-Invasive Continuous Glucose Prediction Models Using Multi-Modal Wearable Sensors in Free-Living Conditions.
Sensors (Basel, Switzerland)
May 20, 2025
Continuous monitoring of glucose levels is important for diabetes management and prevention. While traditional glucose monitoring methods are often invasive and expensive, recent approaches using machine learning (ML) models have explored non-invasiv...
Multivariate Glucose Forecasting Using Deep Multihead Attention Layers Inside Neural Basis Expansion Networks.
IEEE journal of biomedical and health informatics
May 6, 2025
Glucose forecasting is a crucial feature in a closed-loop diabetes management system relying on minimally invasive continuous glucose monitoring (CGM) sensors. Forecasting is required to prevent hyperglycaemia or hypoglycaemia due to delayed or incor...
Predicting isolated impaired glucose tolerance without oral glucose tolerance test using machine learning in Chinese Han men.
Frontiers in endocrinology
Apr 24, 2025
BACKGROUND: Isolated Impaired Glucose Tolerance (I-IGT) represents a specific prediabetic state that typically requires a standardized oral glucose tolerance test (OGTT) for diagnosis. This study aims to predict glucose tolerance status in Chinese Ha...
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