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.
Original language | English (US) |
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Pages (from-to) | 1057 |
Number of pages | 1 |
Journal | AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium |
State | Published - 2008 |
Externally published | Yes |
ASJC Scopus subject areas
- General Medicine