Abstract
We report on an experiment to use the natural language processing tools being developed in the SPECIALIST system to accurately identify terminology associated with the coronary arteries as expressed in coronary catheterization reports. The ultimate goal is to map from any anatomically-oriented medical text to online images, using the UMLS as an intermediate knowledge source. We describe some of the problems encountered when processing coronary artery terminology and report on the results of a formative evaluation of a tool for addressing these problems.
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