A 
system for predicting and summarizing medical events from electronic health records includes a 
computer memory storing aggregated electronic health records from a multitude of patients of diverse age, health conditions, and 
demographics including medications, laboratory values, diagnoses, 
vital signs, and medical notes. The aggregated electronic health records are converted into a single standardized 
data structure format and ordered arrangement per patient, e.g., into a chronological order. A computer (or computer 
system) executes one or more 
deep learning models trained on the aggregated health records to predict one or more future 
clinical events and summarize pertinent past medical events related to the predicted events on an input electronic health 
record of a patient having the standardized 
data structure format and ordered into a chronological order. An electronic device configured with a healthcare provider-facing interface displays the predicted one or more future 
clinical events and the pertinent past medical events of the patient.