Coronary artery disease (CAD) is the most common form of heart disease and has become the primary reason for death. A correct and on-time diagnosis of CAD is very important. Diagnosis of CAD being a strenuous activity, scientists have planned different intelligent diagnostic frameworks for improved CAD diagnosis. Still, low CAD classification accuracy is an issue in these frameworks. In this paper, the authors propose a feature selection technique (FST) that utilizes a genetic algorithm (GA) with J48 classifier as the objective function to choose adequate features for better CAD classification accuracy. After feature removal, classification frameworks are used (i.e., artificial neural network [ANN]) like multilayer perceptron network (MLP), radial basis function network (RBFN), ANN-based ensemble model (ANN-EM), and deep neural network (DNN). Finally, this research proposes an integrated model of GA and ANN-EM for classification of CAD.<\/p>","DOI":"10.4018\/ijcvip.2021070105","type":"journal-article","created":{"date-parts":[[2021,6,21]],"date-time":"2021-06-21T14:23:41Z","timestamp":1624285421000},"page":"70-83","source":"Crossref","is-referenced-by-count":2,"title":["An Ensemble Model With Genetic Algorithm for Classification of Coronary Artery Disease"],"prefix":"10.4018","volume":"11","author":[{"given":"Pratibha","family":"Verma","sequence":"first","affiliation":[{"name":"Dr. C.V. Raman University, Bilaspur, India"}]},{"given":"Vineet Kumar","family":"Awasthi","sequence":"additional","affiliation":[{"name":"Dr. C.V. Raman University, Bilaspur, India"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-5686-7119","authenticated-orcid":true,"given":"Sanat Kumar","family":"Sahu","sequence":"additional","affiliation":[{"name":"Govt. Kaktiya Post Graduate College, Jagdalpur, India"}]}],"member":"2432","container-title":["International Journal of Computer Vision and Image Processing"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=282062","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,6]],"date-time":"2022-05-06T21:02:38Z","timestamp":1651870958000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJCVIP.2021070105"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2021,7,1]]},"references-count":0,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021,7]]}},"URL":"https:\/\/doi.org\/10.4018\/ijcvip.2021070105","relation":{},"ISSN":["2155-6997","2155-6989"],"issn-type":[{"value":"2155-6997","type":"print"},{"value":"2155-6989","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,1]]}}}