title: Syntactical negation detection in clinical practice guidelines.
abstract: In clinical practice guidelines (CPGs) the medical information is stored in a narrative way. A large part of this information occurs in a negated form. The detection of negation in CPGs is an important task since it helps medical personnel to identify not occurring symptoms and diseases as well as treatment actions that should not be accomplished. We developed algorithms capable of Negation Detection in this kind of medical documents. According to our results, we are convinced that the involvement of syntactical methods can improve Negation Detection, not only in medical writings but also in arbitrary narrative texts.
authors.affiliation: Institute of Software Technology and Interactive Systems, Vienna University of Technology, Vienna, Austria. stefan.gindl@gmx.at
authors.forename: Stefan
authors.initials: S
authors.lastname: Gindl
authors.forename: Katharina
authors.initials: K
authors.lastname: Kaiser
authors.forename: Silvia
authors.initials: S
authors.lastname: Miksch
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D006801:Humans; D008495:Medical Oncology; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D017410:Practice Guidelines as Topic; D012660:Semantics; D012984:Software; D017432:Unified Medical Language System