Date of Award
Thesis - Restricted
Master of Science (MS)
Mathematics, Statistics and Computer Science
Struble, Craig A.
Merrill, Stephen J.
The goal of MeSH Association Viewer (MAV) is to utilize association learning to visualize and quantify relationships among physiological, disease related, and treatment related concepts. The bibliographic database MEDLINE is mined to create one-to-one association rules, while keeping track of each relationship's corresponding confidence and support. The MeSH taxonomy is utilized to create rules that represent multiple levels of abstraction. MAV's user interface returns visualizations which SiMAP's physiologists can use to create pathways backed by scientific literature.
Heilman, Kurt, "MeSH Association Viewer: Utilizing Association Learning and a Hierarchical Naive Bayes' Classifier to Graphically Summarize Scientific Literature" (2008). Master's Theses (1922-2009) Access restricted to Marquette Campus. 2152.