In this work, we conducted a two-phase user-study involving patients, caregivers, and clinicians to understand gaps in current approaches that support reflection and user needs for new solutions.
Samuel Morton, Rui Li, Sayanton Dibbo, Temiloluwa Prioleau
In this paper, we employ a data-driven approach to study the relationship between key behavioral factors (sleep, meal size, insulin dose) and proximal diabetic management indicators.
In this paper, we present Neural Physiological Encoder (NPE), a simple module that leverages decomposed convolutional filters to automatically generate effective features that can be used with a downstream neural network for blood glucose prediction.