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dc.contributor.authorPeng, Mingkaien_NZ
dc.contributor.authorSundararajan, Vijayaen_NZ
dc.contributor.authorWilliamson, Tyleren_NZ
dc.contributor.authorMinty, Evan P.en_NZ
dc.contributor.authorSmith, Tony C.en_NZ
dc.contributor.authorDoktorchik, Chelsea T.A.en_NZ
dc.contributor.authorQuan, Hudeen_NZ
dc.date.accessioned2018-05-17T00:02:21Z
dc.date.available2018en_NZ
dc.date.available2018-05-17T00:02:21Z
dc.date.issued2018en_NZ
dc.identifier.citationPeng, M., Sundararajan, V., Williamson, T., Minty, E. P., Smith, T. C., Doktorchik, C. T. A., & Quan, H. (2018). Data on coding association rules from an inpatient administrative health data coded by International classification of disease - 10th revision (ICD-10) codes. Data in Brief, 18, 710–712. https://doi.org/10.1016/j.dib.2018.02.043en
dc.identifier.urihttps://hdl.handle.net/10289/11839
dc.description.abstractData presented in this article relates to the research article entitled “Exploration of association rule mining for coding consistency and completeness assessment in inpatient administrative health data” (Peng et al. [1]) in preparation). We provided a set of ICD-10 coding association rules in the age group of 55 to 65. The rules were extracted from an inpatient administrative health data at five acute care hospitals in Alberta, Canada, using association rule mining. Thresholds of support and confidence for the association rules mining process were set at 0.19% and 50% respectively. The data set contains 426 rules, in which 86 rules are not nested. Data are provided in the supplementary material. The presented coding association rules provide a reference for future researches on the use of association rule mining for data quality assessment.en_NZ
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.rights© 2018 Published by Elsevier Inc. This is an open access article under the CC BY license.
dc.subjectcomputer scienceen_NZ
dc.subjectMachine learning
dc.titleData on coding association rules from an inpatient administrative health data coded by International classification of disease - 10th revision (ICD-10) codesen_NZ
dc.typeJournal Article
dc.identifier.doi10.1016/j.dib.2018.02.043en_NZ
dc.relation.isPartOfData in Briefen_NZ
pubs.begin-page710
pubs.elements-id220737
pubs.end-page712
pubs.publication-statusAccepteden_NZ
pubs.volume18en_NZ
dc.identifier.eissn2352-3409en_NZ


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