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dc.contributor.authorSlater, Luke T
dc.contributor.authorWilliams, John A
dc.contributor.authorKarwath, Andreas
dc.contributor.authorRussell, Sophie
dc.contributor.authorPendleton, Samantha C
dc.contributor.authorFanning, Hilary
dc.contributor.authorBall, Simon
dc.contributor.authorSchofield, Paul
dc.contributor.authorHoehndorf, Robert
dc.contributor.authorGkoutos, Georgios V
dc.date.accessioned2021-06-16T06:10:35Z
dc.date.available2021-06-16T06:10:35Z
dc.date.issued2021-06-15
dc.identifier.citationSlater, L. T., Williams, J. A., Karwath, A., Russell, S., Pendleton, S. C., Fanning, H., … Gkoutos, G. V. (2021). Klarigi: Explanations for Semantic Groupings. doi:10.1101/2021.06.14.448423
dc.identifier.doi10.1101/2021.06.14.448423
dc.identifier.urihttp://hdl.handle.net/10754/669595
dc.description.abstractSemantic annotation facilitates the use of background knowledge in analysis. This includes approaches that sort entities into groups, clusters, or assign labels or outcomes that are typically difficult to derive semantic explanations for. We introduce Klarigi, a tool that creates semantic explanations for groups of entities described by ontology terms implemented in a manner that balances multiple scoring heuristics. We demonstrate Klarigi by using it to identify characteristic terms for text-derived phenotypes of emergency admissions for two frequently conflated diagnoses, pulmonary embolism and pneumonia. Klarigi provides a universal method by which entity groups or labels can be explained semantically, and thus contributes to improved explainability of analysis methods.
dc.publisherCold Spring Harbor Laboratory
dc.relation.urlhttp://biorxiv.org/lookup/doi/10.1101/2021.06.14.448423
dc.relation.urlhttps://www.biorxiv.org/content/biorxiv/early/2021/06/15/2021.06.14.448423.full.pdf
dc.rightsArchived with thanks to Cold Spring Harbor Laboratory
dc.subjectontology
dc.subjectsemantic analysis
dc.subjectmimic-iii
dc.subjecttext mining
dc.subjectcluster explanation
dc.titleKlarigi: Explanations for Semantic Groupings
dc.typePreprint
dc.contributor.departmentComputational Bioscience Research Center, King Abdullah University of Science and Technology, SA
dc.eprint.versionPre-print
dc.contributor.institutionInstitute of Cancer and Genomic Sciences, University of Birmingham, UK
dc.contributor.institutionUniversity Hospitals Birmingham, NHS Foundation Trust,UK
dc.contributor.institutionMRC Health DataResearch UK (HDR UK) Midlands, UK
dc.contributor.institutionDept of Physiology, Development, and Neuroscience, University of Cambridge, UK
kaust.personHoehndorf, Robert T
refterms.dateFOA2021-06-16T06:11:02Z


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