Ontology-driven hypothesis generation to explain anomalous patient responses to treatment

Laura Moss; Derek Sleeman; Malcolm Sim; Malcolm Booth; Malcolm Daniel; Lyndsay Donaldson; Charlotte Gilhooly; Martin Hughes; John Kinsella

doi:10.1007/978-1-84882-983-1_5

Ontology-driven hypothesis generation to explain anomalous patient responses to treatment

Laura Moss, Derek Sleeman, Malcolm Sim, Malcolm Booth, Malcolm Daniel, Lyndsay Donaldson, Charlotte Gilhooly, Martin Hughes, John Kinsella

University of Glasgow

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Within the medical domain there are clear expectations as to how a patient
should respond to treatments administered. When these responses are not observed it can be challenging for clinicians to understand the anomalous responses. The work reported here describes a tool which can detect anomalous patient responses to treatment and further suggest hypotheses to explain the anomaly. In order to develop this tool, we have undertaken a study to determine how Intensive Care Unit (ICU) clinicians identify anomalous patient responses; we then asked further clinicians to provide potential explanations for such anomalies. The high level reasoning deployed by the clinicians has been captured and generalised to form the procedural component of the ontology-driven tool. An evaluation has shown that the tool successfully reproduced the clinician’s hypotheses in the majority of cases. Finally, the paper concludes by describing planned extensions to this work.

Original language	English
Title of host publication	Research and Development in Intelligent Systems XXVI
Subtitle of host publication	Incorporating Applications and Innovations in Intelligent Systems XVII
Editors	Max Bramer, Richard Ellis, Miltos Petridis
Place of Publication	London, United Kingdom
Publisher	Springer-Verlag
Pages	63-76
Number of pages	14
ISBN (Electronic)	978-1848829831
ISBN (Print)	1848829825, 978-1848829824
DOIs	https://doi.org/10.1007/978-1-84882-983-1_5
Publication status	Published - 19 Nov 2009
Event	29th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence (AI-2009) - Cambridge, United Kingdom Duration: 15 Dec 2009 → 17 Dec 2009

Conference

Conference	29th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence (AI-2009)
Country/Territory	United Kingdom
City	Cambridge
Period	15/12/09 → 17/12/09

Bibliographical note

Best Student paper.
Republished in KBS Journal (2010)

Access to Document

10.1007/978-1-84882-983-1_5

Cite this

Moss, L., Sleeman, D., Sim, M., Booth, M., Daniel, M., Donaldson, L., Gilhooly, C., Hughes, M., & Kinsella, J. (2009). Ontology-driven hypothesis generation to explain anomalous patient responses to treatment. In M. Bramer, R. Ellis, & M. Petridis (Eds.), Research and Development in Intelligent Systems XXVI: Incorporating Applications and Innovations in Intelligent Systems XVII (pp. 63-76). Springer-Verlag. https://doi.org/10.1007/978-1-84882-983-1_5

Ontology-driven hypothesis generation to explain anomalous patient responses to treatment. / Moss, Laura; Sleeman, Derek; Sim, Malcolm et al.
Research and Development in Intelligent Systems XXVI: Incorporating Applications and Innovations in Intelligent Systems XVII. ed. / Max Bramer; Richard Ellis; Miltos Petridis. London, United Kingdom: Springer-Verlag, 2009. p. 63-76.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Moss, L, Sleeman, D, Sim, M, Booth, M, Daniel, M, Donaldson, L, Gilhooly, C, Hughes, M & Kinsella, J 2009, Ontology-driven hypothesis generation to explain anomalous patient responses to treatment. in M Bramer, R Ellis & M Petridis (eds), Research and Development in Intelligent Systems XXVI: Incorporating Applications and Innovations in Intelligent Systems XVII. Springer-Verlag, London, United Kingdom, pp. 63-76, 29th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence (AI-2009), Cambridge, United Kingdom, 15/12/09. https://doi.org/10.1007/978-1-84882-983-1_5

Moss L, Sleeman D, Sim M, Booth M, Daniel M, Donaldson L et al. Ontology-driven hypothesis generation to explain anomalous patient responses to treatment. In Bramer M, Ellis R, Petridis M, editors, Research and Development in Intelligent Systems XXVI: Incorporating Applications and Innovations in Intelligent Systems XVII. London, United Kingdom: Springer-Verlag. 2009. p. 63-76 doi: 10.1007/978-1-84882-983-1_5

Moss, Laura ; Sleeman, Derek ; Sim, Malcolm et al. / Ontology-driven hypothesis generation to explain anomalous patient responses to treatment. Research and Development in Intelligent Systems XXVI: Incorporating Applications and Innovations in Intelligent Systems XVII. editor / Max Bramer ; Richard Ellis ; Miltos Petridis. London, United Kingdom : Springer-Verlag, 2009. pp. 63-76

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AU - Gilhooly, Charlotte

AU - Hughes, Martin

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Ontology-driven hypothesis generation to explain anomalous patient responses to treatment

Abstract

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Bibliographical note

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Cite this