Digital Diabetes
This research area focuses on the potential role that innovations such as smart data, artificial intelligence, algorithms, and block chain could play in diabetes technology.
This research area is dedicated to the role of smart data and artificial intelligence (AI), feedback systems such as learning algorithms, machine learning, block chain technology, etc., including artificial pancreas (fully closed loops, hybrid loops, etc.). The networking of input signals to generate biological real-time assessments is central. In addition, algorithms and AI approaches are also used in related areas.
Projects in this focus area
Menstrual Cycle Study: Identifying changes in insulin sensitivity across the menstrual cycle in T1D
DCB and Tidepool are entering a partnership to explore the relationship between diabetes and women’s health. The first...
enhance-d: Enhanced Diabetes Self-Management
Diabetes technology generates a lot of data, but rarely is all this data used to inform action. DCB supports enhance-d...
Qarbs: Accurate results for estimating carbohydrates
Estimating carbohydrates as supreme discipline for people living with diabetes is still depending on gut feelings and...
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