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.