AIMC Topic: Blood Glucose Self-Monitoring

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A multimodal deep learning architecture for predicting interstitial glucose for effective type 2 diabetes management.

Scientific reports Jul 29, 2025
The accurate prediction of blood glucose is critical for the effective management of diabetes. Modern continuous glucose monitoring (CGM) technology enables real-time acquisition of interstitial glucose concentrations, which can be calibrated against...
Humans Neural Networks, Computer Deep Learning Blood Glucose Diabetes Mellitus, Type 2 Blood Glucose Self-Monitoring Female Male Middle Aged
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Predicting postprandial glucose excursions to personalize dietary interventions for type-2 diabetes management.

Scientific reports Jul 17, 2025
Elevated postprandial glucose levels present a global epidemic and a major challenge in type-2 diabetes (T2D) management. A key barrier to developing effective dietary interventions for T2D management is the wide inter-individual variation in glycemi...
Blood Glucose Self-Monitoring Blood Glucose Precision Medicine Diabetes Mellitus, Type 2 Postprandial Period Female Aged Male Middle Aged China Humans Machine Learning
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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...
Blood Glucose Biosensing Techniques Blood Glucose Self-Monitoring Middle Aged Convolutional Neural Networks Fasting Microwaves Humans Neural Networks, Computer Female Adult Male
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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...
Blood Glucose Insulin Diabetes Mellitus, Type 1 Hypoglycemic Agents Humans Pregnancy Evidence Gaps Blood Glucose Self-Monitoring Insulin Infusion Systems Pancreas, Artificial
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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, ...
Sleep Hypoglycemia Wakefulness Blood Glucose Self-Monitoring Wearable Electronic Devices Blood Glucose Diabetes Mellitus, Type 1 Humans Machine Learning Male Algorithms Middle Aged Young Adult Female Adult
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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...
Humans Artificial Intelligence Machine Learning Biomedical Research Blood Glucose Self-Monitoring Blood Glucose Glycemic Control Diabetes Mellitus Bibliometrics
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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...
Prediabetic State Continuous Glucose Monitoring Diabetes Mellitus, Type 2 Blood Glucose Self-Monitoring Disease Management Humans Artificial Intelligence Blood Glucose
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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...
Humans Machine Learning Female Wearable Electronic Devices Blood Glucose Biosensing Techniques Blood Glucose Self-Monitoring Adult Male Middle Aged
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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...
Humans Blood Glucose Neural Networks, Computer Signal Processing, Computer-Assisted Deep Learning Blood Glucose Self-Monitoring
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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...
Diabetes Mellitus Humans Blood Glucose Self-Monitoring Neural Networks, Computer Federated Learning Blood Glucose Machine Learning Biosensing Techniques Photoplethysmography
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