An Improved Strategy for Blood Glucose Control Using Multi-Step Deep Reinforcement Learning
W Gu, S Wang - arXiv preprint arXiv:2403.07566, 2024 - arxiv.org
Blood Glucose (BG) control involves keeping an individual's BG within a healthy range
through extracorporeal insulin injections is an important task for people with type 1 diabetes …
through extracorporeal insulin injections is an important task for people with type 1 diabetes …
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 …
[HTML][HTML] A personalized multitasking framework for real-time prediction of blood glucose levels in type 1 diabetes patients
H Yang, W Li, M Tian, Y Ren - Mathematical Biosciences and …, 2024 - aimspress.com
Real-time prediction of blood glucose levels (BGLs) in individuals with type 1 diabetes (T1D)
presents considerable challenges. Accordingly, we present a personalized multitasking …
presents considerable challenges. Accordingly, we present a personalized multitasking …
Escada: Efficient safety and context aware dose allocation for precision medicine
Finding an optimal individualized treatment regimen is considered one of the most
challenging precision medicine problems. Various patient characteristics influence the …
challenging precision medicine problems. Various patient characteristics influence the …
Machine learning in precision pharmacotherapy of type 2 diabetes—A promising future or a glimpse of hope?
X Zou, Y Liu, L Ji - Digital Health, 2023 - journals.sagepub.com
Precision pharmacotherapy of diabetes requires judicious selection of the optimal
therapeutic agent for individual patients. Artificial intelligence (AI), a swiftly expanding …
therapeutic agent for individual patients. Artificial intelligence (AI), a swiftly expanding …
An Extensive-Form Game Paradigm for Visual Field Testing via Deep Reinforcement Learning
Glaucoma is the leading cause of irreversible but preventable blindness worldwide, and
visual field testing is an important tool for its diagnosis and monitoring. Testing using …
visual field testing is an important tool for its diagnosis and monitoring. Testing using …
Evaluation of Offline Reinforcement Learning for Blood Glucose Level Control in Type 1 Diabetes
Patients with Type 1 diabetes must closely monitor their blood glucose levels and inject
insulin to control them. Automated glucose control methods that remove the need for human …
insulin to control them. Automated glucose control methods that remove the need for human …
Causal prompting model-based offline reinforcement learning
Model-based offline Reinforcement Learning (RL) allows agents to fully utilise pre-collected
datasets without requiring additional or unethical explorations. However, applying model …
datasets without requiring additional or unethical explorations. However, applying model …
Control of type 1 diabetes mellitus using direct reinforcement learning based controller
One of the most challenging area of diabetes research is to provide such automated insulin
delivery systems–so called artificial pancreas systems–that have robust and adaptive …
delivery systems–so called artificial pancreas systems–that have robust and adaptive …
A practical approach based on learning-based model predictive control with minimal prior knowledge of patients for artificial pancreas
MH Lim, S Kim - Computer Methods and Programs in Biomedicine, 2023 - Elsevier
Background and objectives Complete identification of the glucose dynamics for a patient
generally requires prior clinical procedures and several measurements for the patient …
generally requires prior clinical procedures and several measurements for the patient …