{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T00:57:58Z","timestamp":1648515478047},"reference-count":0,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[1995,6]]},"abstract":"<jats:p> A questionnaire, designed to assess bleeding predispositions in tonsillectomy and\/or adenoidectomy patients, was administered to 236 otherwise healthy children. For comparative purposes, 114 patients with bleeding disorders were also studied. An unsupervised non-metric clustering technique was used in an attempt to classify bleeders against non-bleeders based solely on the responses to the questionnaire. Non-metric techniques are essential for the classification process because of the large number of missing attribute values in the patient data set. As a benchmark, a supervised inductive machine learning strategy was also used to classify the patients. <\/jats:p><jats:p> Performance results are compared and contrasted between the techniques across different subsets of the patient data. These techniques are also evaluated as a methodology for determining the relative significance of attributes vis-\u00e0-vis the reduction of the dimensionality of a large medical data set. In this investigation, the classification rate achieved using the non-metric technique (73%) was only marginally poorer than the rate using the supervised technique (76%). Moreover, these results were obtained with an accompanying 80% reduction in the number of attributes used to perform the analysis. <\/jats:p>","DOI":"10.1142\/s0218001495000523","type":"journal-article","created":{"date-parts":[[2004,11,12]],"date-time":"2004-11-12T06:59:25Z","timestamp":1100242765000},"page":"557-564","source":"Crossref","is-referenced-by-count":1,"title":["ASSESSMENT OF BLEEDING PREDISPOSITIONS IN TONSILLECTOMY\/ADENOIDECTOMY PATIENTS USING NON-METRIC CLUSTERING"],"prefix":"10.1142","volume":"09","author":[{"given":"HEATHER","family":"GORDON","sequence":"first","affiliation":[{"name":"Chemical Physics Theory Group, Department of Chemistry, University of Toronto, Toronto, Ontario, Canada M5S 1A1, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"NICOLINO J.","family":"PIZZI","sequence":"additional","affiliation":[{"name":"Informatics Group, Institute for Biodiagnostics, National Research Council of Canada, 435 Ellice Avenue, Winnipeg, Manitoba, Canada R3B 1Y6, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"JON M.","family":"GERRARD","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Health Sciences Centre, University of Manitoba 100 Olivia Street, Winnipeg, Manitoba, Canada R3E 0V9, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"RAY","family":"SOMORJAI","sequence":"additional","affiliation":[{"name":"Informatics Group, Institute for Biodiagnostics, National Research Council of Canada, 435 Ellice Avenue, Winnipeg, Manitoba, Canada R3B 1Y6, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218001495000523","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T12:39:04Z","timestamp":1565181544000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218001495000523"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1995,6]]},"references-count":0,"journal-issue":{"issue":"03","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[1995,6]]}},"alternative-id":["10.1142\/S0218001495000523"],"URL":"https:\/\/doi.org\/10.1142\/s0218001495000523","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"value":"0218-0014","type":"print"},{"value":"1793-6381","type":"electronic"}],"subject":[],"published":{"date-parts":[[1995,6]]}}}