Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/122162
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dc.contributor資管博六-
dc.creator林湘霖-
dc.creatorWang, Chen-Shu;Lin, Shiang-Lin;Chiu, Hui-Chu;Juan, Chun-Jung;He, Xin-Yu;Ting, I-Hsien-
dc.creatorLin, Shiang-Lin-
dc.date2017-10-
dc.date.accessioned2019-01-24T04:39:46Z-
dc.date.available2019-01-24T04:39:46Z-
dc.date.issued2019-01-24T04:39:46Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/122162-
dc.description.abstractThe analytical results induced fifteen representative frequent patterns, these frequent patterns are consists with physicians domain knowledge, and are found very helpful to the existing clinical treatments. Furthermore, compared to the traditional Apriori algorithm, extra 3 to 4 frequent patterns are found via our proposed analysis architecture on average. In additional, compared the performance of stand-alone and map reduce architecture of the proposed architecture, the implementation of our proposed method with three reduces was 12.3% faster in terms of the implementation-time efficiency. Our method may prove extremely helpful in improving doctor-patient relationships and overall health care quality.-
dc.format.extent147 bytes-
dc.format.mimetypetext/html-
dc.relationJournal of Medical Imaging and Health Informatics, Vol.7, No.6, pp.1399-1408-
dc.titleIs a Medical Examination Necessary? Analysis of Medical Examination Transactions through Association Mining Using Multiple Minimum Supports-
dc.typearticle-
dc.doi.urihttps://doi.org/10.1166/jmihi.2017.2254-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextrestricted-
item.openairetypearticle-
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