title: Natural language processing of clinical trial announcements: exploratory-study of building an automated screening application.
abstract: Clinical trials are important for the advancement of medical research. Despite of the benefits clinical trial enrollment is low. We study the feasibility of using NLP to assist with automatic eligibility screening by extracting medical diagnoses from the inclusion and exclusion criteria of cancer clinical trial announcements posted on the internet. We compare the performances of the system versus an oncologist.
authors.affiliation: University of Washington, Seattle, WA, USA.
authors.forename: Imre
authors.initials: I
authors.lastname: Solti
authors.forename: John H
authors.initials: JH
authors.lastname: Gennari
authors.forename: Thomas
authors.initials: T
authors.lastname: Payne
authors.forename: Tom
authors.initials: T
authors.lastname: Payne
authors.forename: Magdolna
authors.initials: M
authors.lastname: Solti
authors.forename: Peter
authors.initials: P
authors.lastname: Tarczy-Hornoch
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D002986:Clinical Trials as Topic / Q000145:classification* / Q000379:methods; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D016347:Medical Records Systems, Computerized / Q000706:statistics & numerical data*; D009323:Natural Language Processing; D009369:Neoplasms / Q000175:diagnosis* / Q000628:therapy*; D018579:Patient Selection; D010363:Pattern Recognition, Automated / Q000379:methods*; D014861:Washington