Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/31540
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dc.contributor.authorCarmichael, Alexander F Ben_UK
dc.contributor.authorBhowmik, Deepayanen_UK
dc.contributor.authorBaily, Johannaen_UK
dc.contributor.authorBrownlow, Andrewen_UK
dc.contributor.authorGunn, George Jen_UK
dc.contributor.authorReeves, Aaronen_UK
dc.date.accessioned2020-08-07T07:09:55Z-
dc.date.available2020-08-07T07:09:55Z-
dc.identifier.urihttp://hdl.handle.net/1893/31540-
dc.description.abstractThis paper proposes Ir-Man (Information Retrieval for Marine Animal Necropsies), a framework for retrieving discrete information from marine mammal post-mortem reports for statistical analysis. When a marine mammal is reported dead after stranding in Scotland, the carcass is examined by the Scottish Marine Animal Strandings Scheme (SMASS) to establish the circumstances of the animal's death. This involves the creation of a 'post-mortem' (or necropsy) report , which systematically describes the body. These semi-structured reports record lesions (damage or abnormalities to anatomical regions) as well as other observations. Observations embedded within these texts are used to determine cause of death. While a cause of death is recorded separately, many other descriptions may be of pathological and epidemiological significance when aggregated and analysed collectively. As manual extraction of these descriptions is costly, time consuming and at times erroneous, there is a need for an automated information retrieval mechanism which is a non-trivial task given the wide variety of possible descriptions, pathologies and species. The Ir-Man framework consists of a new ontology, a lexicon of observations and anatomical terms and an entity relation engine for information retrieval and statistics generation from a pool of necropsy reports. We demonstrate the effectiveness of our framework by creating a rule-based binary classifier for identifying bottlenose dolphin attacks (BDA) in harbour porpoise gross pathology reports and achieved an accuracy of 83.4%.en_UK
dc.language.isoenen_UK
dc.publisherACMen_UK
dc.relationCarmichael AFB, Bhowmik D, Baily J, Brownlow A, Gunn GJ & Reeves A (2020) Ir-Man: An Information Retrieval Framework for Marine Animal Necropsy Analysis. In: 11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB 2020), Virtual, 21.09.2020-24.09.2020. New York: ACM. https://acm-bcb.org/; https://doi.org/10.1145/3388440.3412417en_UK
dc.rights© ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version will be published in the ACM Digital Library as part of ACM-BCB 2020 proceedingsen_UK
dc.subjectInformation retrieval, marine animal, necropsy analysis, ontologyen_UK
dc.titleIr-Man: An Information Retrieval Framework for Marine Animal Necropsy Analysisen_UK
dc.typeConference Paperen_UK
dc.identifier.doi10.1145/3388440.3412417en_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.contributor.funderScotland's Rural Collegeen_UK
dc.identifier.urlhttps://acm-bcb.org/en_UK
dc.author.emaildeepayan.bhowmik@stir.ac.uken_UK
dc.citation.conferencedates2020-09-21 - 2020-09-24en_UK
dc.citation.conferencelocationVirtualen_UK
dc.citation.conferencename11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB 2020)en_UK
dc.publisher.addressNew Yorken_UK
dc.description.notesOutput Status: Forthcomingen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.contributor.affiliationInstitute of Aquacultureen_UK
dc.contributor.affiliationScotland's Rural College (SRUC)en_UK
dc.contributor.affiliationScotland's Rural College (SRUC)en_UK
dc.contributor.affiliationScotland's Rural College (SRUC)en_UK
dc.identifier.wtid1650495en_UK
dc.contributor.orcid0000-0003-1762-1578en_UK
dc.contributor.orcid0000-0002-2242-7078en_UK
dc.date.accepted2020-07-16en_UK
dc.date.filedepositdate2020-08-05en_UK
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings

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