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Knowledge-mediated retrieval of laboratory observations.

C Hsu¹, H S Goldberg

¹Center for Clinical Computing, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.

Proceedings. AMIA Symposium

|November 24, 1999

Summary

We developed an ontology for laboratory observations and a knowledge mediator to make it accessible. This supports intelligent medical applications by clarifying medical concept meanings.

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Area of Science:

Medical Informatics
Biomedical Ontologies
Knowledge Representation

Background:

Intelligent medical applications require standardized medical concept meanings.
Existing systems lack comprehensive, accessible ontologies for laboratory observations.

Purpose of the Study:

To develop a robust ontology for laboratory observations.
To create a knowledge mediator for distributed access to the ontology.
To provide services for retrieving laboratory observations and mapping units of measure.

Main Methods:

Ontology development using established modeling principles.
Implementation of a knowledge mediator architecture.
Development of specific services for data retrieval and unit mapping.
Integration with LOINC (Logical Observation Identifiers Names and Codes) property-types.

Main Results:

A functional ontology for laboratory observations has been created.
Two key services are operational: observation retrieval and unit mapping.
The knowledge mediator facilitates access in a distributed environment.

Conclusions:

The developed ontology and knowledge mediator enhance the usability of laboratory data.
This work provides a foundation for more intelligent medical applications.
Further development can expand the ontology's scope and services.

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