{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T16:34:22Z","timestamp":1759336462118},"reference-count":25,"publisher":"IGI Global","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012,1,1]]},"abstract":"<p>One of the main causes of death the world over is the family of cardiovascular diseases, of which coronary artery disease (CAD) is a major type. Angiography is the principal diagnostic modality for the stenosis of heart arteries; however, it leads to high complications and costs. The present study conducted data-mining algorithms on the Z-Alizadeh Sani dataset, so as to investigate rule based and feature based classifiers and their comparison, and the reason for the effectiveness of a preprocessing algorithm on a dataset. Misclassification of diseased patients has more side effects than that of healthy ones. To this end, this paper employs 10-fold cross-validation on cost-sensitive algorithms along with base classifiers of Na\u00efve Bayes, Sequential Minimal Optimization (SMO), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and C4.5 and the results show that the SMO algorithm yielded very high sensitivity (97.22%) and accuracy (92.09%) rates.<\/p>","DOI":"10.4018\/jkdb.2012010104","type":"journal-article","created":{"date-parts":[[2013,1,29]],"date-time":"2013-01-29T21:03:34Z","timestamp":1359493414000},"page":"59-79","source":"Crossref","is-referenced-by-count":37,"title":["Exerting Cost-Sensitive and Feature Creation Algorithms for Coronary Artery Disease Diagnosis"],"prefix":"10.4018","volume":"3","author":[{"given":"Roohallah","family":"Alizadehsani","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Sharif University of Technology, Tehran, Iran"}]},{"given":"Mohammad Javad","family":"Hosseini","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Sharif University of Technology, Tehran, Iran"}]},{"given":"Reihane","family":"Boghrati","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Sharif University of Technology, Tehran, Iran"}]},{"given":"Asma","family":"Ghandeharioun","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Sharif University of Technology, Tehran, Iran"}]},{"given":"Fahime","family":"Khozeimeh","sequence":"additional","affiliation":[{"name":"Mashhad University of Medical Science, Mashhad, Iran"}]},{"given":"Zahra Alizadeh","family":"Sani","sequence":"additional","affiliation":[{"name":"Tehran University of Medical Science, Tehran, Iran"}]}],"member":"2432","reference":[{"key":"jkdb.2012010104-0","doi-asserted-by":"publisher","DOI":"10.1145\/170036.170072"},{"issue":"4","key":"jkdb.2012010104-1","first-page":"542","article-title":"Diagnosis of coronary artery disease using data mining techniques based on symptoms and ecg features.","volume":"82","author":"R.Alizadehsani","year":"2012","journal-title":"European Journal of Scientific Research"},{"key":"jkdb.2012010104-2","unstructured":"Alizadehsani, R., Habibi, J., Hosseini, M. J., Mashayekhi, H., Boghrati, R., Ghandeharioun, A. Sani, A. Z. (n.d.). A data mining approach for diagnosis of coronary artery disease. Manuscript submitted for publication."},{"key":"jkdb.2012010104-3","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2009.07.055"},{"key":"jkdb.2012010104-4","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-60327-241-4_13"},{"key":"jkdb.2012010104-5","doi-asserted-by":"crossref","unstructured":"Bickel, S., & Scheffer, T. (2004). Multi-view clustering. In Proceedings of the IEEE International Conference on Data Mining, pp. 19\u201326.","DOI":"10.1109\/ICDM.2004.10095"},{"key":"jkdb.2012010104-6","author":"R. 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