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...

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Published inProceedings - Symposium on Computer Application in Medical Care pp. 383 - 387
Main Authors Greenes, R A, McClure, R C, Pattison-Gordon, E, Sato, L
Format Journal Article
LanguageEnglish
Published United States American Medical Informatics Association 1992
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ISSN0195-4210

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Abstract 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.
AbstractList 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.
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.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.
Author Pattison-Gordon, E
Greenes, R A
McClure, R C
Sato, L
AuthorAffiliation Decision Systems Group, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts
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SubjectTerms Diagnosis, Computer-Assisted
Information Systems
Medical Informatics Computing
Semantics
Subject Headings
Unified Medical Language System
Title The findings--diagnosis continuum: implications for image descriptions and clinical databases
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