… deep learning framework for personalized BG prediction, which is called Fast-adaptive and
Confident Neural Network … in deep learning to address the above challenges, including …

… In this work, we propose a new deep learning model using an attention-based evidential …
evidential neural network (E3NN) model to compute the lower bounds (LBs) of each prediction. …

… we propose a novel deep probabilistic model for glucose prediction that explicitly accounts
… blood glucose prediction for type 1 diabetes using evidential deep learning and metalearning…

… Mogren, “Blood glucose prediction with variance estimation using recurrent neural networks,…
Idri, “Deep learning for blood glucose prediction: Cnn vs lstm,” in International Conference …

… While evidential uncertainty estimates for deep learning have been studied for multi-class …
dubious predictions. We achieve this by learning the mapping between the evidential space …

… glucose monitoring (CGM), insulin, dietary, and other relevant information to develop a prediction
model, for example, machine learning … review of personalized blood glucose prediction …

… blood glucose prediction for type 1 diabetes using evidential deep learning and metalearning…
III, “A meta-learning approach to personalized blood glucose prediction in type 1 diabetes,” …

… and strategies of machine learning and a hybrid system focusing on the prediction of BG
dynamics in type 1 diabetes. The review covers machine learning approaches pertinent to the …

… glucose metabolism such as insulinogenic and evidence of βcell-… -driven blood glucose
patterns as well as the prediction of … developed machine learning and deep learning algorithms …

… deep learning (DL) model incorporating multitask learning (MTL) for personalized blood
glucose prediction. … based on relevant evidence from other subjects. In this work, personalized …