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Automated reasoning using abduction for interpretation of medical signals
Örebro University, School of Science and Technology. (AASS)
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-3122-693X
2014 (English)In: Journal of Biomedical Semantics, ISSN 2041-1480, E-ISSN 2041-1480, Vol. 5, 35Article in journal (Refereed) Published
Abstract [en]

This paper proposes an approach to leverage upon existing ontologies in order to automate the annotation of time series medical data. The annotation is achieved by an abductive reasoner using parsimonious covering theorem in order to determine the best explanation or annotation for specific user defined events in the data. The novelty of this approach resides in part by the system’s flexibility in how events are defined by users and later detected by the system. This is achieved via the use of different ontologies which find relations between medical, lexical and numerical concepts. A second contribution resides in the application of an abductive reasoner which uses the online and existing ontologies to provide annotations. The proposed method is evaluated on datasets collected from ICU patients and the generated annotations are compared against those given by medical experts.

Place, publisher, year, edition, pages
BioMed Central, 2014. Vol. 5, 35
Keyword [en]
Knowledge acquisition; Abductive reasoning; Sensor
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:oru:diva-35936DOI: 10.1186/2041-1480-5-35ISI: 000343713100001Scopus ID: 2-s2.0-84950253297OAI: oai:DiVA.org:oru-35936DiVA: diva2:737644
Funder
Swedish Research Council, 2010-4769
Available from: 2014-08-13 Created: 2014-08-13 Last updated: 2017-10-18Bibliographically approved

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Citation style
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  • de-DE
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Output format
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