… 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 …

… from a type 1 diabetes data set. These results may enable a feasible solution with low
computational cost for the time-dependent adjustment of artificial pancreas for diabetes patients. …

Most Type 1 diabetes mellitus (T1DM) patients have … -the-art intelligent technology namely
deep belief network (DBN) … , 15 children with Type 1 diabetes were volunteered overnight. …

… of diabetes by the patients themselves. This work presents an approach based on deep
learning … (1) Convolutional layers act as filters and automatically learn to detect the features of …

… This study has presented a hybrid deep learning model for HbA1c prediction from realistically
imperfect time series of SMBG. While major indicators of HbA1c are well-known and can …

… Diabetes is a group of chronic metabolic disorders that affect almost half a billion people
worldwide 1 , and around 10% of them have type 1 diabetes (T1D) 2 . Due to an absolute …

… Here, we develop DEEP*HLA, a multitask convolutional deep learning method to accurately
impute genotypes of HLA genes from SNV-level data. Through the application to the two …

… Deep learning has been proven to achieve state-of-the-art performance in BG prediction. …
In this work, we introduce a novel deep learning framework to predict BG levels with the edge …

… Modern deep learning models, trained … deep learning approaches is often obtained at the
expense of less interpretability. To surpass this limit, in this work we propose a new deep learn…

… the state-of-the-art machine learning strategies and their hybrid system focusing on BG …
in people with type 1 diabetes. The review covers machine learning approaches pertinent to …