title: A statistical natural language processor for medical reports.
abstract: Statistical natural language processors have been the focus of much research during the past decade. The main advantage of such an approach over grammatical rule-based approaches is its scalability to new domains. We present a statistical NLP for the domain of radiology and report on methods of knowledge acquisition, parsing, semantic interpretation, and evaluation. Preliminary performance data are given. A discussion of the perceived benefit, limitations and future work is presented.
authors.affiliation: Department of Radiology, Children's Hospital, Seattle, WA 98105, USA.
authors.forename: R K
authors.initials: RK
authors.lastname: Taira
authors.forename: S G
authors.initials: SG
authors.lastname: Soderland
mesh_terms: D000465:Algorithms; D005069:Evaluation Studies as Topic; D006801:Humans; D008037:Linguistics; D008499:Medical Records; D009323:Natural Language Processing; D013902:Radiography, Thoracic; D012660:Semantics