AI Medical Compendium Topic

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Blood Glucose

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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
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.

Classification of glucose-level in deionized water using machine learning models and data pre-processing technique.

PloS one
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...

Hybrid CNN-GRU Model for Real-Time Blood Glucose Forecasting: Enhancing IoT-Based Diabetes Management with AI.

Sensors (Basel, Switzerland)
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...

Developing an AI-Based clinical decision support system for basal insulin titration in type 2 diabetes in primary Care: A Mixed-Methods evaluation using heuristic Analysis, user Feedback, and eye tracking.

International journal of medical informatics
BACKGROUND AND AIM: The progressive nature of type 2 diabetes often, in time, necessitates basal insulin therapy to achieve glycemic targets. However, despite standardized titration algorithms, many people remain poorly controlled after initiating in...

Mixed-effects neural network modelling to predict longitudinal trends in fasting plasma glucose.

BMC medical research methodology
BACKGROUND: Accurate fasting plasma glucose (FPG) trend prediction is important for management and treatment of patients with type 2 diabetes mellitus (T2DM), a globally prevalent chronic disease. (Generalised) linear mixed-effects (LME) models and m...

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
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...

Non-invasive blood glucose monitoring using PPG signals with various deep learning models and implementation using TinyML.

Scientific reports
Accurate and continuous blood glucose monitoring is essential for effective diabetes management, yet traditional finger pricking methods are often inconvenient and painful. To address this issue, photoplethysmography (PPG) presents a promising non-in...