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Projects
The studies that make up DAQIQ, past and present: how people live with diabetes, and the analytics and AI that make care individualised.
Living with Diabetes in Qatar: the LDQ Cohort
A five-year cohort following adults with type 2 diabetes across four care settings, to learn how digital and AI advice shapes diabetes distress and self-management.
AI-driven healthcare surveillance and proactive care recommendation in smart environments
AI that brings together data from connected health devices and clinical knowledge to spot changes early and recommend timely, personalised care for people living with diabetes.
Longitudinal analysis of risk factors associated with diabetes using multimodal data and machine learning
PhD research that fused bone scans, retinal images, ECG, genetic, laboratory and lifestyle data from Qatar Biobank to predict who will develop type 2 diabetes, and to study its complications.
Aain-D: AI for diabetic retinopathy from retinal images
AI that grades diabetic retinopathy from retinal photographs, including a new Radon-transform method released as open-source software.
Harnessing the power of artificial intelligence: predicting type 2 diabetes onset
PhD research showing that combining retinal images, ECG features and clinical risk factors improves prediction of type 2 diabetes in Qatar, and introducing new open-source image methods.
C.P.-Support: peer support for people living with diabetes
An intelligent peer-support platform connecting people who manage chronic conditions such as diabetes, so they can learn from each other’s experience.
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