{"title":"Comparison of SVM and k-NN classifiers in the estimation of the state of the arteriovenous fistula problem","authors":"Marcin Grochowina, L. Leniowska","doi":"10.15439/2015F194","DOIUrl":null,"url":null,"abstract":"The paper presents a concise report on the comparison of the classifiers k-NN and SVM in the case of a fuzzy classification of the arterio-venous fistula based on audio recordings. What has been used in the studies are the acoustic signals taken from both healthy patients as well as those diagnosed with the narrowing of a fistula in a mild and major degree of stenosis. In the publication there have been selected two features, each presenting one- time and frequency domain, which enable a quite clear depiction of the classification result. The aim of the study is to develop a solution enabling the detection of fistula's pathologies at an early stage.","PeriodicalId":276884,"journal":{"name":"2015 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Federated Conference on Computer Science and Information Systems (FedCSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15439/2015F194","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
The paper presents a concise report on the comparison of the classifiers k-NN and SVM in the case of a fuzzy classification of the arterio-venous fistula based on audio recordings. What has been used in the studies are the acoustic signals taken from both healthy patients as well as those diagnosed with the narrowing of a fistula in a mild and major degree of stenosis. In the publication there have been selected two features, each presenting one- time and frequency domain, which enable a quite clear depiction of the classification result. The aim of the study is to develop a solution enabling the detection of fistula's pathologies at an early stage.