Artificial Intelligence for Glucose Modelling and Prediction in Diabetes Care

Dear Colleagues,

Diabetes has in just a few decades become one of the major diseases around the world. The number of people with diabetes quadrupled from 1980 to 2014 (108 to 422 million) with a death toll of 4.2 million in 2019. Today, diabetes is the major cause of stroke, heart attacks, blindness, kidney failure, and lower limb amputation.

Numerous efforts have been made to provide advanced solutions to measure, analyze, and predict glycemic and related factors to coach patients but also to provide medical practitioners with platforms to monitor this type of chronic disease.

In recent years, smart sensors, the Internet of Things, and Artificial Intelligence have triggered a revolution in this field. In particular, advances in deep learning models, transfer learning, as well the acceptability and interpretability of these models, have allowed them to achieve an impressive performance. These technological advances are transforming diabetes care from early diagnosis to risk modeling and complication monitoring.

This Special Issue is intended to provide an up-to-date and comprehensive view of recent progress in Artificial Intelligence applied to diabetes care.

Potential topics include but are not limited to:

• Diabetes diagnosis
• Blood sugar modeling and prediction
• Physical activity and emotion analysis for diabetes
• Nutritional analysis
• Patients’ self-management and coaching
• Risk modelling
• Complication monitoring
• Genomics for diabetes
• Emerging trends in deep learning techniques
• Physiological models for diabetes assessment
• Smart sensing and IoT
• Multisensor data fusion
• Intelligent data acquisition and measurement systems
• Cloud and embedded computing
• Human/machine smart interfaces

Prof. Mehdi Ammi
Prof. Mounim A. El Yacoubi
Guest Editors

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