Open-source natural language processing system for named entity recognition in clinical text of electronic health records. CliNER will identify clinically-relevant entities mentioned in a clinical narrative (such as diseases/disorders, signs/symptoms, medications, procedures, etc). Requires annotated data such as the i2b2 2010 NLP data set.
Anna Rumshisky, Tristan Neumann, William Boag, Kevin Wacome.
Text Machine Lab for NLP, Dept of Computer Science, UMass Lowell