The vast amount of data stored in a patient’s Electronic Medical Record (EMR) makes it difficult for clinicians to get the information they need. A Learning EMR uses machine learning to predict which data a clinician is likely to seek and highlights those data on the EMR user interface. In this poster, we report insights into what, where, and when data should be highlighted, and how training data should be collected for a Learning EMR.

Learning Objective: To learn insights into what, when, and where a Learning EMR should highlight patient data and how to collect training data.


Andrew King (Presenter)
University of Pittsburgh

Shyam Visweswaran, University of Pittsburgh
Harry Hochheiser, University of Pittsburgh
Gilles Clermont, University of Pittsburgh
Gregory Cooper, University of Pittsburgh

Presentation Materials: