Abdullah Çalıskan, H. Badem, A. Basturk, M. E. Yuksel
{"title":"The effect of autoencoders over reducing the dimensionality of a dermatology data set","authors":"Abdullah Çalıskan, H. Badem, A. Basturk, M. E. Yuksel","doi":"10.1109/TIPTEKNO.2016.7863101","DOIUrl":null,"url":null,"abstract":"The effect of using autoencoders for dimensionality reduction of a medical data set is investigated. A stack of two autoencoders has been trained for popular benchmark medical data set for dermatological disease diagnosis. The improvement of the presented approach has been visualized by the Principal Component Analysis method. Results shows that the use of a autoencoders significantly improves the accuracy of dermatological disease diagnosis.","PeriodicalId":431660,"journal":{"name":"2016 Medical Technologies National Congress (TIPTEKNO)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Medical Technologies National Congress (TIPTEKNO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TIPTEKNO.2016.7863101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The effect of using autoencoders for dimensionality reduction of a medical data set is investigated. A stack of two autoencoders has been trained for popular benchmark medical data set for dermatological disease diagnosis. The improvement of the presented approach has been visualized by the Principal Component Analysis method. Results shows that the use of a autoencoders significantly improves the accuracy of dermatological disease diagnosis.
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