DocumentCode
3195101
Title
Ontologies for knowledge representation in a computer-based patient record
Author
Bayegan, Elisabeth ; Nytrø, Øystein ; Grimsmo, Anders
Author_Institution
Dept. of Comput. & Inf. Sci., Norwegian Univ. of Sci. & Technol., Trondheim, Norway
fYear
2002
fDate
2002
Firstpage
114
Lastpage
121
Abstract
In contrast to existing patient-record systems, which merely offer static applications for storage and presentation, a helpful patient-record system is a problem-oriented, knowledge-based system, which provides clinicians with situation-dependent information. We propose a practical approach to extend the current data model with (1) means to recognize and interpret situations, (2) knowledge of how clinicians work and what information they need, and (3) means to rank information according to its relevance in a given care situation. Following the methodology of second-generation knowledge-based systems, that use ontologies to define fundamental concepts, their properties, and interrelationships within a particular domain, we present an ontology that supports three prerequisite features for a future helpful patient-record system: a family-care workflow process, a problem-oriented patient record, and means to identify relevant information to the care process and medical problems.
Keywords
knowledge based systems; knowledge representation; medical administrative data processing; problem solving; computer-based patient record; helpful patient-record system; knowledge representation; ontologies; problem-oriented knowledge-based system; problem-oriented patient record; second-generation knowledge-based systems; situation-dependent information; Application software; Data mining; Data models; Diagnostic expert systems; Information science; Knowledge based systems; Knowledge representation; Medical diagnostic imaging; Medical expert systems; Ontologies;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings. 14th IEEE International Conference on
ISSN
1082-3409
Print_ISBN
0-7695-1849-4
Type
conf
DOI
10.1109/TAI.2002.1180795
Filename
1180795
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