Abstract
Natural language processing and text mining (“BioNLP”) are branches of biomedical informatics that deal with processing prose, whether in journal articles or electronic medical records, for purposes such as extracting information, cohort retrieval, and other uses. They are made difficult by the rampant presence of ambiguity and variability in human-produced prose. In addition, biomedical text poses special challenges on a number of levels. Machine learning and rule-based approaches both have a long history in biomedical natural language processing, and hybrid systems are common. Much progress has been made in biomedical natural language processing and text mining in recent years, and the field is poised for explosive growth as new resources should become available in the near future. Many open opportunities for research remain.
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