title: Visualization of health information with predications extracted using natural language processing and filtered using the UMLS.
abstract: Increased availability of and reliance on written health information can tax the abilities of unskilled readers. We are developing a system that uses natural language processing to extract phrases, identify medical terms using the UMLS, and visualize the propositions. This system substantially reduces the amount of information a consumer must read, while providing an alternative to traditional prose based text.
authors.affiliation: School of Information Systems & Technology, Claremont Graduate University, Claremont, California, USA.
authors.forename: Trudi
authors.initials: T
authors.lastname: Miller
authors.forename: Gondy
authors.initials: G
authors.lastname: Leroy
mesh_terms: D001185:Artificial Intelligence; D002140:California; D003194:Computer-Assisted Instruction / Q000379:methods*; D054626:Consumer Health Information / Q000379:methods*; D003626:Data Display; D016247:Information Storage and Retrieval; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated; D017432:Unified Medical Language System; D014584:User-Computer Interface