AIMC Topic: Diabetes Mellitus, Type 1
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Stress Testing of an Artificial Pancreas System With Pizza and Exercise Leads to Improvements in the System's Fuzzy Logic Controller.
Journal of diabetes science and technology
Sep 14, 2015
BACKGROUND: Under controlled conditions, the Dose Safety artificial pancreas (AP) system controller, which utilizes "fuzzy logic" (FL) methodology to calculate and deliver appropriate insulin dosages based on changes in blood glucose, successfully ma...
Dietary Carbohydrates
Dietary Fats
Insulin Infusion Systems
Pancreas, Artificial
Exercise
Blood Glucose
Insulin
Time Factors
Diabetes Mellitus, Type 1
Hypoglycemic Agents
Treatment Outcome
Fuzzy Logic
Reproducibility of Results
Young Adult
Adult
Male
Materials Testing
Humans
Blood Glucose Self-Monitoring
Algorithms
Drug Dosage Calculations
Female
Stress, Physiological
Predictive Value of Tests
Equipment Design
Signal Processing, Computer-Assisted
Comparative assessment of glucose prediction models for patients with type 1 diabetes mellitus applying sensors for glucose and physical activity monitoring.
Medical & biological engineering & computing
Jun 7, 2015
The present work presents the comparative assessment of four glucose prediction models for patients with type 1 diabetes mellitus (T1DM) using data from sensors monitoring blood glucose concentration. The four models are based on a feedforward neural...
Diabetes knowledge in young adults: associations with hemoglobin A1C.
Families, systems & health : the journal of collaborative family healthcare
Jan 19, 2015
The purpose of this study was to quantify associations between hemoglobin A1C (A1C) and diabetes knowledge score using an assessment tool developed to evaluate the level of diabetes knowledge in young adults with Type 1 diabetes (T1DM) and their pare...
Integration of multi-omics data and machine learning to identify antioxidant biomarkers in type 1 diabetes.
Free radical biology & medicine
Aug 16, 2025
The identification of biomarkers for early diagnosis and monitoring the progression of Type 1 Diabetes (T1DM) is essential for improving disease management. This study integrates multi-omics data with machine learning to identify antioxidant stress p...
Comparing Deterministic and Stochastic Reinforcement Learning for Glucose Regulation in Type 1 Diabetes.
Studies in health technology and informatics
Aug 7, 2025
Type 1 Diabetes (T1D) is a chronic condition affecting millions worldwide, requiring external insulin administration to regulate blood glucose levels and prevent serious complications. Artificial Pancreas Systems (APS) for managing T1D currently rely...
Research Gaps, Challenges, and Opportunities in Automated Insulin Delivery Systems.
Diabetes technology & therapeutics
Jul 1, 2025
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 longer, healthie...
The Use of Continuous Glucose Monitoring to Diagnose Stage 2 Type 1 Diabetes.
Journal of diabetes science and technology
Jul 1, 2025
This consensus report evaluates the potential role of continuous glucose monitoring (CGM) in screening for stage 2 type 1 diabetes (T1D). CGM offers a minimally invasive alternative to venous blood testing for detecting dysglycemia, facilitating earl...
Neural Networks for On-Chip Model Predictive Control: A Method to Build Optimized Training Datasets and its Application to Type-1 Diabetes.
IEEE transactions on cybernetics
Jul 1, 2025
Training neural networks (NNs) to behave as model predictive control (MPC) algorithms is an effective way to implement them in constrained embedded devices. By collecting large amounts of input-output data, where inputs represent system states and ou...
Deep reinforcement learning for Type 1 Diabetes: Dual PPO controller for personalized insulin management.
Computers in biology and medicine
Jun 1, 2025
BACKGROUND: Managing blood glucose levels in Type 1 Diabetes Mellitus (T1DM) is essential to prevent complications. Traditional insulin delivery methods often require significant patient involvement, limiting automation. Reinforcement Learning (RL)-b...
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