{"title":"Classification of thrombosis collagen diseases based on C4.5 algorithm","authors":"S. Soliman, Safia Abbas, A. M. Salem","doi":"10.1109/INTELCIS.2015.7397209","DOIUrl":null,"url":null,"abstract":"Recently, collagen diseases propagated due to many factors such as pressure and pollution. Thrombosis is one of the most famous collagen diseases that obstruct the blood flow causing vital complications for crucial parts of the circulatory system. Such diseases cause a high risk for the doctors due to the huge number of the laboratory examinations and the efforts to diagnosis. Accordingly, this paper implements C4.5 algorithm, as one of the most famous data mining techniques, on real thrombosis dataset. The dataset was collected from Chiba University as a challenging dataset for thrombosis diagnosis. The results show that the C4.5 could diagnose the thrombosis degree with accuracy 98.4%.","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INTELCIS.2015.7397209","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Recently, collagen diseases propagated due to many factors such as pressure and pollution. Thrombosis is one of the most famous collagen diseases that obstruct the blood flow causing vital complications for crucial parts of the circulatory system. Such diseases cause a high risk for the doctors due to the huge number of the laboratory examinations and the efforts to diagnosis. Accordingly, this paper implements C4.5 algorithm, as one of the most famous data mining techniques, on real thrombosis dataset. The dataset was collected from Chiba University as a challenging dataset for thrombosis diagnosis. The results show that the C4.5 could diagnose the thrombosis degree with accuracy 98.4%.