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the sole unified numeric index of all known drugs, biologically active agents, diseases & empirical statements of all effective clinical outcomes published in the United States National Library of Medicine. the Visual Medical Dictionary is a network visualization illustrating the relationships between diseases (purple), drugs & therapies (orange), & bio-agents (green). edge thickness reflects the strength of the relationship, while alpha-transparency shows a positive outcome score (i.e. darker is more positive).

[link: curehunter.com|via visualcomplexity.com]

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2 COMMENTS

Interesting vis, though I'm not too sure how useful it is to us in the health sector because it's not clear how they determine the strength of relationships. Infovis-wise, I guess it could also be improved by using the position of linked elements (rotational angle and distance) to convey information too.

Thu 22 Nov 2007 at 9:53 PM

As the CEO of CureHunter and an architect on the system, I have a vested interest to declare up front--but Kieren's comment/post
raises a good question. If you will go to the main home page for the site: www.curehunter.com
you will see the physician's interface. The strengths of the graph relationships are determined by the frequency with which a successful clinical outcome is reported in the peer-reviewed literature and the strength of the specific clinical outcome on a scale of 1-10. For example, a drug that consistently achieves "complete remission" for a cancer might be rated 8 on the scale, and one
where patients showed only marginal improvement and tumors continued to metastasize might be 0-1, if some marginal gain was noted in clinical trial. The AI-based weighting system generally passes the Turing Test with real physicians, a fact which allows the underlying graph data to be directed and used in discovery models and real time evidence-based medicine Clinical Decision Support Systems--where the graphs help the most evidence-supported meds be selected. In theory, this will improve the rate of positive patient outcomes overall. I hope that helps a little. See also, the National Science Foundation Conference: http://biomedweb.info where I will be directing 2 panels on the modeling methods in CureHunter. Thanks for commenting. The Graph Theory in
CureHunter is somewhat the tip of an iceberg and I know it opens up a lot of scientific questions for deeper scrutiny and intelligent scepticism.

Judge

Sun 02 Dec 2007 at 11:43 AM
Judge M. Schonfeld
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