Artificial intelligence (AI) algorithms in combination with continuous monitoring technologies
have the potential to revolutionize chronic disease management. The recent innovations in …

Background: Machine learning (ML) models provide more choices to patients with diabetes
mellitus (DM) to more properly manage blood glucose (BG) levels. However, because of …

(1) Background: the use of machine learning techniques for the purpose of anticipating
hypoglycemia has increased considerably in the past few years. Hypoglycemia is the drop in …

Diabetes mellitus is characterized by elevated blood glucose levels, however patients with
diabetes may also develop hypoglycemia due to treatment. There is an increasing demand …

Background and objective Hypoglycemia is a key barrier to achieving optimal glycemic
control in people with diabetes, which has been proven to cause a set of deleterious …

Diabetes, a metabolic disorder disease, can cause short-term acute or even long-term
chronic complications in a patient's body. In 2021, 10.5% of the world's adult population had …

Background: Machine learning (ML) algorithms have been widely introduced to diabetes
research including those for the identification of hypoglycemia. Objective: The objective of …

Abstract Background Diabetes Mellitus outpatients would benefit from a lifestyle support tool
that delivers reliable short term Blood Glucose Level (BGL) predictions. Aim To develop a …

This work sought to explore the potential of using standalone continuous glucose monitor
(CGM) data for the prediction of hypoglycemia utilizing a large cohort of type 1 diabetes …

Type 1 diabetes mellitus (T1D) is a chronic disease that, if not treated properly, can lead to
serious complications. We propose a layered meta-learning approach based on multi-expert …