Using natural language processing to provide personalized learning opportunities from trainee clinical notes.

Objective: Assessment of medical trainee learning through pre-defined competencies is now commonplace in schools of medicine. We describe a novel electronic advisor system using natural language processing (NLP) to identify two geriatric medicine competencies from medical student clinical notes in the electronic medical record: advance directives (AD) and altered mental status (AMS).

Materials And Methods: Clinical notes from third year medical students were processed using a general-purpose NLP system to identify biomedical concepts and their section context.