Artificial intelligence and machine learning for improving glycemic control in diabetes: best practices, pitfalls, and opportunities
Objective: Artificial intelligence and machine learning are transforming many fields including
medicine. In diabetes, robust biosensing technologies and automated insulin delivery …
medicine. In diabetes, robust biosensing technologies and automated insulin delivery …
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 …
Short-term prediction method of blood glucose based on temporal multi-head attention mechanism for diabetic patients
The hyperglycemic state of people with diabetes can lead to metabolic and healthy
disturbances in the body. Diabetes is mainly treated clinically by conservative treatment …
disturbances in the body. Diabetes is mainly treated clinically by conservative treatment …
Convolutional recurrent neural networks for glucose prediction
Control of blood glucose is essential for diabetes management. Current digital therapeutic
approaches for subjects with type 1 diabetes mellitus such as the artificial pancreas and …
approaches for subjects with type 1 diabetes mellitus such as the artificial pancreas and …
Minimally invasive electrochemical continuous glucose monitoring sensors: Recent progress and perspective
Diabetes and its complications are seriously threatening the health and well-being of
hundreds of millions of people. Glucose levels are essential indicators of the health …
hundreds of millions of people. Glucose levels are essential indicators of the health …
Stacked LSTM based deep recurrent neural network with kalman smoothing for blood glucose prediction
Background Blood glucose (BG) management is crucial for type-1 diabetes patients
resulting in the necessity of reliable artificial pancreas or insulin infusion systems. In recent …
resulting in the necessity of reliable artificial pancreas or insulin infusion systems. In recent …
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 …
The importance of interpreting machine learning models for blood glucose prediction in diabetes: an analysis using SHAP
Abstract Machine learning has become a popular tool for learning models of complex
dynamics from biomedical data. In Type 1 Diabetes (T1D) management, these models are …
dynamics from biomedical data. In Type 1 Diabetes (T1D) management, these models are …
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 …
Blood glucose prediction with variance estimation using recurrent neural networks
J Martinsson, A Schliep, B Eliasson… - Journal of Healthcare …, 2020 - Springer
Many factors affect blood glucose levels in type 1 diabetics, several of which vary largely
both in magnitude and delay of the effect. Modern rapid-acting insulins generally have a …
both in magnitude and delay of the effect. Modern rapid-acting insulins generally have a …