Abstract: A method for determining a treatment recommendation using a multi-armed bandit (MAB) model can include receiving first patient information, determining, using the MAB model, the treatment recommendation based on the first patient information, wherein the MAB model is trained based on a MAB treatment recommendation determined by the MAB model using second patient information and a clinical treatment recommendation determined according to clinical guidelines based on the second patient information, and providing the treatment recommendation.

Abstract: Various embodiments of the present disclosure provide signal interpretation and data aggregation techniques for generating predictive insights for a user. The techniques may include receiving initial physiological features for a user that are based on recorded sensor values for the user. The techniques include generating activity encodings for the user based on interaction data objects for the user and generating a combined input feature vector by aggregating the initial physiological features and the activity encodings. The techniques include generating, using a machine learning model, a physiological prediction for the user based on the combined input feature vector.