{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T12:45:25Z","timestamp":1777725925888,"version":"3.51.4"},"reference-count":20,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2011,6,1]],"date-time":"2011-06-01T00:00:00Z","timestamp":1306886400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Int Med Res"],"published-print":{"date-parts":[[2011,6]]},"abstract":"<jats:p>Mitral valve prolapse (MVP) has been described as one of the most common cardiac valvular abnormalities in industrialized countries, and can result in sudden death. This study focused on various feature selection mechanisms that might improve the predictive power of a classifier to diagnose MVP. The experiment included selection mechanisms using classical greedy feature selection approaches (forward selection and backward elimination), a genetic algorithm (GA) approach and a cellular automaton (CA) approach. The main aim of this latest approach is to use CA with GA for the data transformation phase of the knowledge discovery process. The CA\u2014GA approach produced better results than the classical greedy approaches. The subsets of features produced by the GA and CA approaches were most appropriate for the decision tree classifier, for diagnosing MVP with the highest overall class accuracy. More importantly, the CA and GA approaches were also capable of generalizing some important knowledge concerning MVP diagnosis.<\/jats:p>","DOI":"10.1177\/147323001103900342","type":"journal-article","created":{"date-parts":[[2013,2,27]],"date-time":"2013-02-27T14:22:55Z","timestamp":1361974975000},"page":"1075-1083","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Diagnosing Mitral Valve Prolapse by Improving the Predictive Power of Classifiers"],"prefix":"10.1177","volume":"39","author":[{"given":"D","family":"Dinevski","sequence":"first","affiliation":[{"name":"Faculty of Medicine, University of Maribor, Maribor, Slovenia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M","family":"Mertik","sequence":"additional","affiliation":[{"name":"Faculty of Information Studies in Novo Mesto, Slovenia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"P","family":"Kokol","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, University of Maribor, Maribor, Slovenia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2011,6,1]]},"reference":[{"key":"bibr1-147323001103900342","doi-asserted-by":"publisher","DOI":"10.1056\/NEJM198703123161109"},{"key":"bibr2-147323001103900342","doi-asserted-by":"publisher","DOI":"10.1007\/0-387-25465-X_52"},{"key":"bibr3-147323001103900342","doi-asserted-by":"publisher","DOI":"10.1007\/BF00153759"},{"key":"bibr4-147323001103900342","first-page":"9","volume-title":"Advances in Knowledge Discovery and Data Mining","author":"Brachman R","year":"1996"},{"key":"bibr5-147323001103900342","doi-asserted-by":"publisher","DOI":"10.1016\/B978-1-55860-200-7.50027-1"},{"key":"bibr6-147323001103900342","doi-asserted-by":"publisher","DOI":"10.1056\/NEJM198904203201609"},{"key":"bibr7-147323001103900342","doi-asserted-by":"publisher","DOI":"10.1016\/0002-8703(83)90704-4"},{"key":"bibr8-147323001103900342","doi-asserted-by":"publisher","DOI":"10.7326\/0003-4819-111-4-305"},{"key":"bibr9-147323001103900342","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-08-050058-4.50007-3"},{"key":"bibr10-147323001103900342","volume-title":"Clinician's Illustrated Dictionary of Cardiology","author":"Anderson RH","year":"1991","edition":"2"},{"key":"bibr11-147323001103900342","doi-asserted-by":"publisher","DOI":"10.1016\/0002-8703(63)90375-2"},{"key":"bibr12-147323001103900342","doi-asserted-by":"publisher","DOI":"10.1016\/0002-8703(87)90956-2"},{"key":"bibr13-147323001103900342","doi-asserted-by":"publisher","DOI":"10.1056\/NEJM198209233071302"},{"key":"bibr14-147323001103900342","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-36599-0_21"},{"key":"bibr15-147323001103900342","doi-asserted-by":"publisher","DOI":"10.1023\/A:1011996210207"},{"key":"bibr16-147323001103900342","volume-title":"Genetic Algorithms in Search, Optimization, and Machine Learning","author":"Goldberg DE","year":"1989"},{"key":"bibr17-147323001103900342","doi-asserted-by":"publisher","DOI":"10.1016\/0167-2789(84)90245-8"},{"key":"bibr18-147323001103900342","first-page":"214","volume-title":"Wheels, Life, and Other Mathematical Amusements","author":"Gardner M","year":"1983"},{"key":"bibr19-147323001103900342","first-page":"177","volume-title":"Advances in Genetic Programming","author":"D'Haeseleer P","year":"1994"},{"key":"bibr20-147323001103900342","doi-asserted-by":"crossref","unstructured":"Mierswa I, Wurst M, Klinkenberg R, YALE: rapid prototyping for complex data mining tasks.\n                      Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-06)\n                      , 2006 (available at: http:\/\/rapid-i.com\/content\/view\/30\/214\/lang,en\/).","DOI":"10.1145\/1150402.1150531"}],"container-title":["Journal of International Medical Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/147323001103900342","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/147323001103900342","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T10:44:12Z","timestamp":1777459452000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/147323001103900342"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011,6]]},"references-count":20,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2011,6]]}},"alternative-id":["10.1177\/147323001103900342"],"URL":"https:\/\/doi.org\/10.1177\/147323001103900342","relation":{},"ISSN":["0300-0605","1473-2300"],"issn-type":[{"value":"0300-0605","type":"print"},{"value":"1473-2300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2011,6]]}}}