Background: We implement a high-resolution visualization of the medical knowledge domain using the self-organizing map (SOM) method, based on a corpus of over two million publications. While self-organizing maps have been used for document visualization for some time, (1) little is known about how to deal with truly large document collections in conjunction with a large number of SOM neurons, (2) post-training geometric and semiotic transformations of the SOM tend to be limited, and (3) no user studies have been conducted with domain experts to validate the utility and readability of the resulting visualizations. Our study makes key contributions to all of these issues.
Skupin et al. REF use over two million publications to depict a detailed landscape of the medical knowledge field.
Visualizing the Topical Structure of the Medical Sciences: A Self-Organizing Map Approach
PLoS ONE
PLoS ONE
Medicine Physics