Analyzing Differences in Operational Disease Definitions Using Ontological Modeling

Authors:
Linda Peelen;Michel C. Klein;Stefan Schlobach;Nicolette F. Keizer;Niels Peek
Affiliations:
Dept. of Medical Informatics, Academic Medical Center, Amsterdam,;Dept. of Artificial Intelligence, Vrije Universiteit Amsterdam,;Dept. of Artificial Intelligence, Vrije Universiteit Amsterdam,;Dept. of Medical Informatics, Academic Medical Center, Amsterdam,;Dept. of Medical Informatics, Academic Medical Center, Amsterdam,
Venue:
AIME '07 Proceedings of the 11th conference on Artificial Intelligence in Medicine
Year:
2007

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Abstract

In medicine, there are many diseases which cannot be precisely characterized but are considered as natural kinds. In the communication between health care professionals, this is generally not problematic. In biomedical research, however, crisp definitions are required to unambiguously distinguish patients with and without the disease. In practice, this results in different operational definitions being in use for a single disease. This paper presents an approach to compare different operational definitions of a single disease using ontological modeling. The approach is illustrated with a case-study in the area of severe sepsis.