Analyzing differences in operational disease definitions using ontological modeling

Linda Peelen; Michel C.A. Klein; Stefan Schlobach; Nicolette F. De Keizer; Niels Peek

doi:10.1007/978-3-540-73599-1_40

Analyzing differences in operational disease definitions using ontological modeling

Linda Peelen^*
, Michel C.A. Klein
, Stefan Schlobach
, Nicolette F. De Keizer
, Niels Peek

^*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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.

Original language	English
Title of host publication	Artificial Intelligence in Medicine - 11th Conference on Artificial Intelligence in Medicine, AIME 2007, Proceedings
Publisher	Springer/Verlag
Pages	297-302
Number of pages	6
Volume	4594
ISBN (Print)	3540735984, 9783540735984
DOIs	https://doi.org/10.1007/978-3-540-73599-1_40
Publication status	Published - 2007
Event	11th Conference on Artificial Intelligence in Medicine, AIME 2007 - Amsterdam, Netherlands Duration: 7 Jul 2007 → 11 Jul 2007

Conference

Conference	11th Conference on Artificial Intelligence in Medicine, AIME 2007
Country/Territory	Netherlands
City	Amsterdam
Period	7/07/07 → 11/07/07

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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Peelen, L., Klein, M. C. A., Schlobach, S., De Keizer, N. F., & Peek, N. (2007). Analyzing differences in operational disease definitions using ontological modeling. In Artificial Intelligence in Medicine - 11th Conference on Artificial Intelligence in Medicine, AIME 2007, Proceedings (Vol. 4594, pp. 297-302). Springer/Verlag. https://doi.org/10.1007/978-3-540-73599-1_40

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title = "Analyzing differences in operational disease definitions using ontological modeling",

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.",

author = "Linda Peelen and Klein, \{Michel C.A.\} and Stefan Schlobach and \{De Keizer\}, \{Nicolette F.\} and Niels Peek",

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booktitle = "Artificial Intelligence in Medicine - 11th Conference on Artificial Intelligence in Medicine, AIME 2007, Proceedings",

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note = "11th Conference on Artificial Intelligence in Medicine, AIME 2007 ; Conference date: 07-07-2007 Through 11-07-2007",

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Peelen, L, Klein, MCA , Schlobach, S, De Keizer, NF & Peek, N 2007, Analyzing differences in operational disease definitions using ontological modeling. in Artificial Intelligence in Medicine - 11th Conference on Artificial Intelligence in Medicine, AIME 2007, Proceedings. vol. 4594, Springer/Verlag, pp. 297-302, 11th Conference on Artificial Intelligence in Medicine, AIME 2007, Amsterdam, Netherlands, 7/07/07. https://doi.org/10.1007/978-3-540-73599-1_40

Analyzing differences in operational disease definitions using ontological modeling. / Peelen, Linda; Klein, Michel C.A.; Schlobach, Stefan et al.
Artificial Intelligence in Medicine - 11th Conference on Artificial Intelligence in Medicine, AIME 2007, Proceedings. Vol. 4594 Springer/Verlag, 2007. p. 297-302.

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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AU - De Keizer, Nicolette F.

AU - Peek, Niels

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AB - 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.

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T2 - 11th Conference on Artificial Intelligence in Medicine, AIME 2007

Y2 - 7 July 2007 through 11 July 2007

ER -

Analyzing differences in operational disease definitions using ontological modeling

Abstract

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UN SDGs

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