“The model was trained with an input window of the five previous data points to forecast the next 96 time steps per sample. The batch size was set to 32, and the learning rate was optimized to ...

Abstract: People with Type 1 diabetes (T1D) require regular exogenous infusion ... These results show that the use of deep reinforcement learning is a viable approach for closed-loop glucose control ...

Interdisciplinary Graduate Program in Quantitative Biosciences, Georgia Institute of Technology, Atlanta, Georgia 30332, United States School of Chemistry and Biochemistry, Georgia Institute of ...

Hypoglycemia is a serious complication in individuals with type 2 diabetes mellitus ... Nine clinically relevant features were analyzed using five machine learning models. The performance of the ...

This study aimed to identify clinically relevant predictors of pancreatic cancer using a supervised machine learning approach and to develop ... Older patients with increased glycated hemoglobin (new ...

Abstract: Number of women with advanced maternal age is increasing along with some preexisting medical condition like diabetes. The objective of this paper is to use machine learning models to predict ...