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Wiharto Wiharto
Department of informatic, Sebelas Maret University

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System Diagnosis of Coronary Heart Disease using A Combination of Dimensional Reduction and Data Mining Techniques: A Review Wiharto Wiharto; Hari Kusnanto; Herianto Herianto
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 2: August 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i2.pp514-523

Abstract

Coronary heart disease is a disease with the highest mortality rates in the world. This makes the development of the diagnostic system as a very interesting topic in the field of biomedical informatics, aiming to detect whether a heart is normal or not. In the literature there are diagnostic system models by combining dimension reduction and data mining techniques. Unfortunately, there are no review papers that discuss and analyze the themes to date. This study reviews articles within the period 2009-2016, with a focus on dimension reduction methods and data mining techniques, validated using a dataset of UCI repository. Methods of dimension reduction use feature selection and feature extraction techniques, while data mining techniques include classification, prediction, clustering, and association rules.
Co-Authors Hari Kusnanto Herianto Herianto