Abstract:Diabetes mellitus is a long term chronicle disorder with a high prevalence rate worldwide. Con-tinuous blood glucose and lifestyle monitoring enabled the control of blood glucose dynamics through machine learning applications using data created by various popular sensors. This survey aims to assess various classical time series, neural networks and state-of-the-art regression models based on a wide variety of machine learning techniques to predict blood glucose and hy-per/hypoglycemia in Type 1 diabetic patien… Show more
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