{"title":"一种基于RNN分类器的心脏病检测系统架构","authors":"Volkan Göreke","doi":"10.58190/icat.2023.14","DOIUrl":null,"url":null,"abstract":"Diagnosing heart disease is a challenging process for physicians. Insufficient number of experts, late diagnosis and misdiagnosis are the difficulties in this process. To overcome these difficulties, systems based on artificial intelligence are used today. Appropriate system selection and obtaining sufficient data sets are a challenge for researchers. In this study, a high-performance CAD architecture was proposed for the detection of heart disease. The proposed architecture has shown a higher performance than the studies carried out using the UCI dataset in the literature.","PeriodicalId":20592,"journal":{"name":"PROCEEDINGS OF THE III INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES IN MATERIALS SCIENCE, MECHANICAL AND AUTOMATION ENGINEERING: MIP: Engineering-III – 2021","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A System Architecture Based on The RNN Classifier for Heart Disease Detection\",\"authors\":\"Volkan Göreke\",\"doi\":\"10.58190/icat.2023.14\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Diagnosing heart disease is a challenging process for physicians. Insufficient number of experts, late diagnosis and misdiagnosis are the difficulties in this process. To overcome these difficulties, systems based on artificial intelligence are used today. Appropriate system selection and obtaining sufficient data sets are a challenge for researchers. In this study, a high-performance CAD architecture was proposed for the detection of heart disease. The proposed architecture has shown a higher performance than the studies carried out using the UCI dataset in the literature.\",\"PeriodicalId\":20592,\"journal\":{\"name\":\"PROCEEDINGS OF THE III INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES IN MATERIALS SCIENCE, MECHANICAL AND AUTOMATION ENGINEERING: MIP: Engineering-III – 2021\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PROCEEDINGS OF THE III INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES IN MATERIALS SCIENCE, MECHANICAL AND AUTOMATION ENGINEERING: MIP: Engineering-III – 2021\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.58190/icat.2023.14\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PROCEEDINGS OF THE III INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES IN MATERIALS SCIENCE, MECHANICAL AND AUTOMATION ENGINEERING: MIP: Engineering-III – 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.58190/icat.2023.14","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A System Architecture Based on The RNN Classifier for Heart Disease Detection
Diagnosing heart disease is a challenging process for physicians. Insufficient number of experts, late diagnosis and misdiagnosis are the difficulties in this process. To overcome these difficulties, systems based on artificial intelligence are used today. Appropriate system selection and obtaining sufficient data sets are a challenge for researchers. In this study, a high-performance CAD architecture was proposed for the detection of heart disease. The proposed architecture has shown a higher performance than the studies carried out using the UCI dataset in the literature.