title: DiseaseAtlas: multi-facet visual analytics for online disease articles.
abstract: Online health information portals provide valuable content to casual consumers. However, the page-oriented nature of these resources makes it difficult for users to understand the overall information space and navigate the complex relationships between various diseases. We have developed a visual analytic system named DiseaseAtlas that helps users navigate a large set of disease-related documents and understand multi-dimensional relationships for key semantic concepts such as symptoms and treatments. This paper describes several unique aspects of DiseaseAtlas and demonstrates its capabilities through a case study.
authors.affiliation: IBM Research, Switzerland.
authors.forename: Jimeng
authors.initials: J
authors.lastname: Sun
authors.forename: David
authors.initials: D
authors.lastname: Gotz
authors.forename: Nan
authors.initials: N
authors.lastname: Cao
mesh_terms: D003196:Computer Graphics; D057225:Data Mining / Q000379:methods*; D004194:Disease; D004282:Documentation / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D009323:Natural Language Processing; D010353:Patient Education as Topic / Q000379:methods*; D014584:User-Computer Interface