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The largest collection of medical evidence in the world is PubMed. However,the significant barrier in accessing and extracting information is informationorganization. A factor that contributes towards this barrier is managingmedical controlled vocabularies that allow us to systematically andconsistently organize, index, and search biomedical literature. Additionally,from users' perspective, to ultimately improve access, visualization is likelyto play a powerful role. There is a strong link between informationorganization and information visualization, as many powerful visualizationsdepend on clustering methods. To improve visualization, therefore, one has todevelop concrete and scalable measures for vocabularies used in indexing andtheir impact on document clustering. The focus of this study is on thedevelopment and evaluation of clustering methods. The paper concludes withdemonstration of downstream network visualizations and their impact ondiscovering potentially valuable and latent genetic and molecular associations.

Measures of Cluster Informativeness for Medical Evidence Aggregation and Dissemination