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A Study of Concept Extraction Across Different Types of Clinical Notes
2015
AMIA Annual Symposium Proceedings
Our research investigates methods for creating effective concept extractors for specialty clinical notes. First, we present three new "specialty area" datasets consisting of Cardiology, Neurology, and Orthopedics clinical notes manually annotated with medical concepts. We analyze the medical concepts in each dataset and compare with the widely used i2b2 2010 corpus. Second, we create several types of concept extraction models and examine the effects of training supervised learners with
pmid:26958209
pmcid:PMC4765588
fatcat:zeki4hfkongllaw5owsb744m4y