title: Comparing syntactic complexity in medical and non-medical corpora.
abstract: With the growing use of Natural Language Processing (NLP) techniques as solutions in Medical Informatics, the need to quickly and efficiently create the knowledge structures used by these systems has grown concurrently. Automatic discovery of a lexicon for use by an NLP system through machine learning will require information about the syntax of medical language. Understanding the syntactic differences between medical and non-medical corpora may allow more efficient acquisition of a lexicon. Three experiments designed to quantify the syntactic differences in medical and non-medical corpora were conducted. The results show that the syntax of medical language shows less variation than non-medical language and is likely simpler. The differences were great enough to question the applicability of general language tools on medical language. These differences may reduce the difficulty of some free text machine learning problems by capitalizing on the simpler nature of narrative medical syntax.
authors.affiliation: Department of Medical Informatics, Columbia University, USA.
authors.forename: D A
authors.initials: DA
authors.lastname: Campbell
authors.forename: S B
authors.initials: SB
authors.lastname: Johnson
mesh_terms: D001185:Artificial Intelligence; D008037:Linguistics; D008091:Literature; D009323:Natural Language Processing