"Units of Meaning" in Medical Documents: Natural Language Processing Perspective
Dimitri Popolov, Joseph R. Barr · 2014
This paper discusses principles for the design of natural language processing (NLP) systems to automatically extract of data from doctor's notes, laboratory results and other medical documents in free-form text. We argue that rather than searching for 'atom units of meaning' in the text and then trying to generalize them into a broader set of documents through increasingly complicated system of rules, an NLP practitioner should take concepts as a whole as a meaningful unit of text. This simplifies the rules and makes NLP system easier to maintain and adapt. The departure point is purely practical, however a deeper investigation of typical problems with the implementation of such systems leads us to a discussion of broader theoretical principles underlying the NLP practices.