An insulin bolus advisor for type 1 diabetes using deep reinforcement learning
(1) Background: People living with type 1 diabetes (T1D) require self-management to
maintain blood glucose (BG) levels in a therapeutic range through the delivery of exogenous …
maintain blood glucose (BG) levels in a therapeutic range through the delivery of exogenous …
Reinforcement learning for blood glucose control: Challenges and opportunities
Individuals with type 1 diabetes (T1D) lack the ability to produce the insulin their bodies
need. As a result, they must continually make decisions about how much insulin to self …
need. As a result, they must continually make decisions about how much insulin to self …
Optimized glycemic control of type 2 diabetes with reinforcement learning: a proof-of-concept trial
G Wang, X Liu, Z Ying, G Yang, Z Chen, Z Liu… - Nature Medicine, 2023 - nature.com
The personalized titration and optimization of insulin regimens for treatment of type 2
diabetes (T2D) are resource-demanding healthcare tasks. Here we propose a model-based …
diabetes (T2D) are resource-demanding healthcare tasks. Here we propose a model-based …
A blood glucose control framework based on reinforcement learning with safety and interpretability: In silico validation
Controlling blood glucose levels in diabetic patients is important for managing their health
and quality of life. Several algorithms based on model predictive control and reinforcement …
and quality of life. Several algorithms based on model predictive control and reinforcement …
A personalized and adaptive insulin bolus calculator based on double deep q-learning to improve type 1 diabetes management
Mealtime insulin dosing is a major challenge for people living with type 1 diabetes (T1D).
This task is typically performed using a standard formula that, despite containing some …
This task is typically performed using a standard formula that, despite containing some …
Deep reinforcement learning for closed-loop blood glucose control
I Fox, J Lee, R Pop-Busui… - Machine Learning for …, 2020 - proceedings.mlr.press
People with type 1 diabetes (T1D) lack the ability to produce the insulin their bodies need.
As a result, they must continually make decisions about how much insulin to self-administer …
As a result, they must continually make decisions about how much insulin to self-administer …
Offline deep reinforcement learning and off-policy evaluation for personalized basal insulin control in type 1 diabetes
Recent advancements in hybrid closed-loop systems, also known as the artificial pancreas
(AP), have been shown to optimize glucose control and reduce the self-management …
(AP), have been shown to optimize glucose control and reduce the self-management …
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 …
Basal Glucose Control in Type 1 Diabetes Using Deep Reinforcement Learning: An In Silico Validation
People with Type 1 diabetes (T1D) require regular exogenous infusion of insulin to maintain
their blood glucose concentration in a therapeutically adequate target range. Although the …
their blood glucose concentration in a therapeutically adequate target range. Although the …
Reinforcement learning-based adaptive insulin advisor for individuals with type 1 diabetes patients under multiple daily injections therapy
Q Sun, MV Jankovic… - 2019 41st Annual …, 2019 - ieeexplore.ieee.org
The existing adaptive basal-bolus advisor (ABBA) was further developed to benefit patients
under insulin therapy with multiple daily injections (MDI). Three different in silico …
under insulin therapy with multiple daily injections (MDI). Three different in silico …