A system is provided including a data pipeline and a model pipeline. A data pipeline includes: an input that receives a first dataset representing categorical features and a second dataset representing numerical features; a feature ingestion block that generates an output corresponding to a sum of the first dataset with the second dataset; an output that provides training labels based on a processing of the summed datasets to predict a temporally isolated and discrete event; and a label creation block that receives the output and generates labels for date features in the first dataset. A model pipeline includes a neural network(s) that: receives a first input corresponding to a summation of non learned date embedding with learned feature embedding; and contextualizes the summation by date embedding historical patient data into the summation. The model pipeline includes a prediction block that receives the contextualized summation and predicts one or more outcomes.