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dc.contributor.authorPiovesan, Luca
dc.contributor.authorSpiotta, Matteo
dc.contributor.authorTerenziani, Paolo
dc.contributor.authorDupre, Daniele Theseider
dc.date.accessioned2020-01-03T01:56:48Z
dc.date.available2020-01-03T01:56:48Z
dc.date.issued2018
dc.identifier.issn0933-1875
dc.identifier.doi10.1007/s13218-018-0540-1
dc.identifier.urihttp://hdl.handle.net/10072/390015
dc.description.abstractIn this paper, we present an approach where Answer Set Programming is used for analyzing the conformance of execution traces, describing the treatment of individual patients, to Computer-Interpretable Guidelines (CIGs) in the medical domain. The problem is challenging because the CIG for a given pathology describes the most typical treatments for that pathology and cannot take into account all the specific cases that may occur for a specific patient, being them contraindications, temporary conditions of the patient, or other major pathologies. Deviations (also in the timing) from a single guideline may then be explainable using general medical knowledge or knowledge about the interaction between pathologies or treatments.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofpagefrom201
dc.relation.ispartofpageto204
dc.relation.ispartofissue2-3
dc.relation.ispartofjournalKI - Künstliche Intelligenz
dc.relation.ispartofvolume32
dc.subject.keywordsScience & Technology
dc.subject.keywordsTechnology
dc.subject.keywordsComputer Science, Artificial Intelligence
dc.titleASP for Conformance Analysis and Explanation of Clinical Guidelines Execution
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationPiovesan, L; Spiotta, M; Terenziani, P; Dupre, DT, ASP for Conformance Analysis and Explanation of Clinical Guidelines Execution, KI - Künstliche Intelligenz, 2018, 32 (2-3), pp. 201-204
dc.date.updated2020-01-03T01:53:49Z
gro.hasfulltextNo Full Text
gro.griffith.authorTerenziani, Paolo


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