Challenges and perspectives for the future of diabetes epidemiology in the era of digital health and artificial intelligence

Abstract Digital health data, for example from social media or connected devices, as well as the artificial intelligence methods to analyze them, are profoundly changing the way we approach research in diabetes epidemiology. The concepts of deep digital phenotyping and digital twins, which are based on the development of large cohort studies of extremely well characterized people with diabetes, will make it possible to further personalize the monitoring and management of the disease, thanks to a better integration of the impact of diabetes on people's daily lives. Similarly, the development of digital biomarkers, such as vocal biomarkers, will improve the remote monitoring of people with diabetes and thus allow the development of the telemonitoring and telemedicine of the future. These new opportunities are promising but they also come with their share of technical and ethical challenges that should not be overlooked.