Visualization of health information with predications extracted using natural language processing and filtered using the UMLS.
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.
Miller
Trudi
T
School of Information Systems & Technology, Claremont Graduate University, Claremont, California, USA.
Leroy
Gondy
G
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