The findings--diagnosis continuum: implications for image descriptions and clinical databases.
As part of the Unified Medical Language System (UMLS) project, we have been exploring the use of semantic net representation to build a medical ontology that can adapt to the needs and perspective of differing kinds of users with varying purposes. A principal objective is to facilitate indexing and retrieval of objects in a variety of target databases, using their own source vocabularies, while maintaining the representation of concepts to which these source vocabularies refer in a single consistent form, so that retrievals that span resource types can be accommodated. In addition, a particular area of deficiency of the existing UMLS Metathesaurus is that of clinical findings, a part of the problem being the multiple alternative views and granularity levels at which clinical findings are described in different target databases. The problem is particularly obvious when one examines the way in which image findings are described, which may be at a purely perceptual level, or at varying levels of aggregation into higher level observations or interpretations. We have developed a recursive model for representing observations and interpretations in a semantic net along a continuum of degree of aggregation, that appears to lend itself well to adaptation to varying perspectives.
Greenes
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Decision Systems Group, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts.
McClure
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Pattison-Gordon
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Sato
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D003936:Diagnosis, Computer-Assisted; D007256:Information Systems; D008492:Medical Informatics Computing; D012660:Semantics; D013358:Subject Headings; D017432:Unified Medical Language System