Anticipating and intervening in nocturnal hypoglycemic episodes

A computer-implemented method for reducing likelihood of a person experiencing nocturnal hypoglycemia, the method comprising:

• extracting a plurality of features including glucose-derived features from continuous glucose monitor (CGM) data, activity-derived features from physical-activity data, and demographic-derived features associated with the person;
• inputting the plurality of features into a neural network configured to output parameters of a probability distribution representing both a predicted minimum overnight glucose value and an associated predictive uncertainty;
• determining, based on output of the neural network, whether a probability that the person's glucose level will fall below a specified hypoglycemic level within a specified time period during an upcoming sleep session meets or exceeds a predetermined risk threshold;
• and
• in response to determining that the probability meets or exceeds the predetermined risk threshold indicative of a predicted hypoglycemia event, causing a display, on a user interface of a mobile computing device, of a personalized bedtime snack recommendation configured to allow the person to avoid the predicted hypoglycemia event.