Uncovering personalized glucose responses and circadian rhythms from multiple wearable biosensors with Bayesian dynamical modeling
ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium) (pw: 1234)Abstract: Wearable biosensors measure physiological variables with high temporal resolution over multiple days and are increasingly employed in clinical settings, such as continuous glucose monitoring in diabetes care. Such datasets …