Large-scale identification of aortic stenosis and its severity using natural language processing on electronic health records.

A validated NLP algorithm applied to a systemwide echocardiography database was substantially more accurate than diagnosis codes for identifying AS. Leveraging machine learning-based approaches on unstructured electronic health record data can facilitate more effective individual and population management than using administrative data alone.