922-P: Diabits—An AI-Powered Smartphone Application for Blood Glucose Monitoring and Predictions

This paper presents DiaBits, an iPhone application that allows patients with diabetes to efficiently monitor and manage their blood glucose levels in real time. Using current CGM data, smartphone sensor data, and user inputs, DiaBits takes advantage of modern machine learning techniques to predict future blood glucose fluctuations up to 60 minutes in advance. These predictions, which are over 95% clinically acceptable according to standard Error Grid Analysis methods, give the patients an opportunity to take corrective action in advance in order to keep their blood glucose values within normal range. Additionally, the presence of predictive alarms and statistical tools for analysis of past data makes it easier for the users to manage their condition and have better blood glucose control. The paper discusses some of the details of the predictive approach, provides accuracy results for 1.63 million predictions made for free-living users of the application, gives a detailed overview of the available features and the interface of DiaBits, and describes some challenges related to using machine learning for real-time predictions of blood glucose behavior.