[HTML][HTML] Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes

AZ Woldaregay, E Årsand, S Walderhaug… - Artificial intelligence in …, 2019 - Elsevier
Background Diabetes mellitus (DM) is a metabolic disorder that causes abnormal blood
glucose (BG) regulation that might result in short and long-term health complications and …

Reinforcement learning application in diabetes blood glucose control: A systematic review

M Tejedor, AZ Woldaregay, F Godtliebsen - Artificial intelligence in …, 2020 - Elsevier
Background Reinforcement learning (RL) is a computational approach to understanding and
automating goal-directed learning and decision-making. It is designed for problems which …

The importance of interpreting machine learning models for blood glucose prediction in diabetes: an analysis using SHAP

F Prendin, J Pavan, G Cappon, S Del Favero… - Scientific reports, 2023 - nature.com
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 …

Short-term prediction method of blood glucose based on temporal multi-head attention mechanism for diabetic patients

G Yang, S Liu, Y Li, L He - Biomedical Signal Processing and Control, 2023 - Elsevier
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 …

Convolutional recurrent neural networks for glucose prediction

K Li, J Daniels, C Liu, P Herrero… - IEEE journal of …, 2019 - ieeexplore.ieee.org
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 …

Deep transfer learning and data augmentation improve glucose levels prediction in type 2 diabetes patients

Y Deng, L Lu, L Aponte, AM Angelidi, V Novak… - NPJ Digital …, 2021 - nature.com
Accurate prediction of blood glucose variations in type 2 diabetes (T2D) will facilitate better
glycemic control and decrease the occurrence of hypoglycemic episodes as well as the …

Personalized blood glucose prediction for type 1 diabetes using evidential deep learning and meta-learning

T Zhu, K Li, P Herrero… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
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 …

GluNet: A deep learning framework for accurate glucose forecasting

K Li, C Liu, T Zhu, P Herrero… - IEEE journal of …, 2019 - ieeexplore.ieee.org
For people with Type 1 diabetes (T1D), forecasting of blood glucose (BG) can be used to
effectively avoid hyperglycemia, hypoglycemia and associated complications. The latest …

[HTML][HTML] Advanced diabetes management using artificial intelligence and continuous glucose monitoring sensors

M Vettoretti, G Cappon, A Facchinetti, G Sparacino - Sensors, 2020 - mdpi.com
Wearable continuous glucose monitoring (CGM) sensors are revolutionizing the treatment of
type 1 diabetes (T1D). These sensors provide in real-time, every 1–5 min, the current blood …

Feature-based machine learning model for real-time hypoglycemia prediction

D Dave, DJ DeSalvo, B Haridas… - Journal of Diabetes …, 2021 - journals.sagepub.com
Background: Hypoglycemia is a serious health concern in youth with type 1 diabetes (T1D).
Real-time data from continuous glucose monitoring (CGM) can be used to predict …