Ontology-driven hypothesis generation to explain anomalous patient responses to treatment |
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Authors: | Laura Moss Derek Sleeman Malcolm Sim Malcolm Booth Malcolm Daniel Lyndsay Donaldson Charlotte Gilhooly Martin Hughes John Kinsella |
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Affiliation: | 1. Institute of Systems and Synthetic Biology, University of Evry-Val-d’Essonne, F-91030 Evry, France;2. University of Lorraine, LORIA, Campus Scientifique, BP 239, 54506 Vandoeuvre-lès-Nancy, France;3. University Clermont Auvergne, CNRS, LIMOS, F-63000 Clermont-Ferrand, France |
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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. |
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