[HTML][HTML] A comprehensive review of models and nonlinear control strategies for blood glucose regulation in artificial pancreas
An autoimmune disease known as type 1 diabetes occurs when the immune system
mistakenly attacks and destroys the beta cells in the pancreas, impairing their ability to …
mistakenly attacks and destroys the beta cells in the pancreas, impairing their ability to …
[HTML][HTML] Co-designing opportunities for Human-Centred Machine Learning in supporting Type 1 diabetes decision-making
Abstract Type 1 Diabetes (T1D) self-management requires hundreds of daily decisions.
Diabetes technologies that use machine learning have significant potential to simplify this …
Diabetes technologies that use machine learning have significant potential to simplify this …
Evaluation of blood glucose level control in type 1 diabetic patients using deep reinforcement learning
Diabetes mellitus is a disease associated with abnormally high levels of blood glucose due
to a lack of insulin. Combining an insulin pump and continuous glucose monitor with a …
to a lack of insulin. Combining an insulin pump and continuous glucose monitor with a …
A New Glycemic closed-loop control based on Dyna-Q for Type-1-Diabetes
Abstract Objective: Type 1 Diabetes Mellitus is an autoimmune disease which requires
constant care from patients. Continuous Glucose Monitoring (CGM) devices allow to keep …
constant care from patients. Continuous Glucose Monitoring (CGM) devices allow to keep …
Learning control-ready forecasters for Blood Glucose Management
Abstract Type 1 diabetes (T1D) presents a significant health challenge, requiring patients to
actively manage their blood glucose (BG) levels through regular bolus insulin …
actively manage their blood glucose (BG) levels through regular bolus insulin …
Evaluating Deep Q-Learning Algorithms for Controlling Blood Glucose in In Silico Type 1 Diabetes
Patients with type 1 diabetes must continually decide how much insulin to inject before each
meal to maintain blood glucose levels within a healthy range. Recent research has worked …
meal to maintain blood glucose levels within a healthy range. Recent research has worked …
Optimizing Blood Glucose Control through Reward Sha** in Reinforcement Learning
FS Rad, J Li - 2023 IEEE International Conference on E-health …, 2023 - ieeexplore.ieee.org
Achieving optimal blood glucose control is a complex challenge for individuals with
diabetes, necessitating a delicate balance among insulin dosage, food consumption …
diabetes, necessitating a delicate balance among insulin dosage, food consumption …
Safe reinforcement learning for automatic insulin delivery in type i diabetes
Despite promising performances, reinforcement learning (RL) is only rarely applied when a
high level of risk is implied. Glycemia control in type I diabetes is one such example: a …
high level of risk is implied. Glycemia control in type I diabetes is one such example: a …
End-to-end offline reinforcement learning for glycemia control
T Beolet, A Adenis, E Huneker, M Louis - Artificial Intelligence in Medicine, 2024 - Elsevier
The development of closed-loop systems for glycemia control in type I diabetes relies
heavily on simulated patients. Improving the performances and adaptability of these close …
heavily on simulated patients. Improving the performances and adaptability of these close …
Deep Reinforcement Learning Control of Type-1 Diabetes with Cross-Patient Generalization
MMH Atanasious, V Becchetti… - … on Control and …, 2024 - ieeexplore.ieee.org
Type 1 diabetes is one of the major concerns in current medical studies, as the World Health
Organisation plans to reduce mortality due to such disease by one third by 2030. Standard …
Organisation plans to reduce mortality due to such disease by one third by 2030. Standard …