Deep learning for diabetes: a systematic review
Diabetes is a chronic metabolic disorder that affects an estimated 463 million people
worldwide. Aiming to improve the treatment of people with diabetes, digital health has been …
worldwide. Aiming to improve the treatment of people with diabetes, digital health has been …
Machine learning techniques for hypoglycemia prediction: trends and challenges
(1) Background: the use of machine learning techniques for the purpose of anticipating
hypoglycemia has increased considerably in the past few years. Hypoglycemia is the drop in …
hypoglycemia has increased considerably in the past few years. Hypoglycemia is the drop in …
IoMT-enabled real-time blood glucose prediction with deep learning and edge computing
Blood glucose (BG) prediction is essential to the success of glycemic control in type 1
diabetes (T1D) management. Empowered by the recent development of the Internet of …
diabetes (T1D) management. Empowered by the recent development of the Internet of …
Enhancing self-management in type 1 diabetes with wearables and deep learning
People living with type 1 diabetes (T1D) require lifelong self-management to maintain
glucose levels in a safe range. Failure to do so can lead to adverse glycemic events with …
glucose levels in a safe range. Failure to do so can lead to adverse glycemic events with …
Personalized blood glucose prediction for type 1 diabetes using evidential deep learning and meta-learning
The availability of large amounts of data from continuous glucose monitoring (CGM),
together with the latest advances in deep learning techniques, have opened the door to a …
together with the latest advances in deep learning techniques, have opened the door to a …
Electronic health records based reinforcement learning for treatment optimizing
Abstract Electronic Health Records (EHRs) have become one of the main sources of
evidence to evaluate clinical actions, improve medical quality, predict disease-risk, and …
evidence to evaluate clinical actions, improve medical quality, predict disease-risk, and …
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 …
[HTML][HTML] Offline reinforcement learning for safer blood glucose control in people with type 1 diabetes
The widespread adoption of effective hybrid closed loop systems would represent an
important milestone of care for people living with type 1 diabetes (T1D). These devices …
important milestone of care for people living with type 1 diabetes (T1D). These devices …
[PDF][PDF] Control engineering methods for blood glucose levels regulation
In this article, we review recently proposed, advanced methods, for the control of blood
glucose levels, in patients with type 1 diabetes. The proposed methods are based on …
glucose levels, in patients with type 1 diabetes. The proposed methods are based on …
Reinforcement learning models and algorithms for diabetes management
With the advancements in reinforcement learning (RL), new variants of this artificial
intelligence approach have been introduced in the literature. This has led to increased …
intelligence approach have been introduced in the literature. This has led to increased …