Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/51539
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dc.contributor.authorPatcharaporn Paokantaen_US
dc.contributor.authorMichele Ceccarellien_US
dc.contributor.authorNapat Harnpornchaien_US
dc.contributor.authorNopasit Chakpitaken_US
dc.contributor.authorSomdet Srichairatanakoolen_US
dc.date.accessioned2018-09-04T06:03:53Z-
dc.date.available2018-09-04T06:03:53Z-
dc.date.issued2012-02-01en_US
dc.identifier.issn1881803Xen_US
dc.identifier.other2-s2.0-84856953354en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84856953354&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/51539-
dc.description.abstractRule induction has played an important role in implementing a medical expert system in the past decade, especially the Thalassemia Expert System. Due to the fact that Thalassemia indicators used in diagnosising types of Thalassemia are very complex, the induction rules C5.0 and Classification and Regression Tree (CART) will be used to elicit new information about Thalassemia. The results obtained from using both algorithms show the different rules separating types of this disease. In the future, these results will be used to develop the Thalassemia Expert System and these results will be compared to find a suitable algorithm. Other algorithms will also be considered. © 2012 ICIC International.en_US
dc.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.titleRule induction for screening Thalassemia using machine learning techniques: C5.0 and CARTen_US
dc.typeJournalen_US
article.title.sourcetitleICIC Express Lettersen_US
article.volume6en_US
article.stream.affiliationsCollege of Artsen_US
article.stream.affiliationsUniversita degli Studi del Sannioen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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