文章基本信息

标题：A Survey on Hybrid Evolutionary Classification Techniques for Medical Diagnosis
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作者：Suman Muwal ; Narender Kumar
期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2016
卷号：5
期号：4
页码：1134-1139
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Knowledge is the important part of human life. There are number of data mining systems that are available today and have many challenges in this field. Today, this is mostly used in the medical diagnosis area to conquer the diagnosis time and to enhance the performance. In medical system, heart disease is the main cause of death for both men and women. That's why early detection of heart disease is necessary. Different types of classification techniques are available in data mining to resolve this problem like Decision tree, C4.5, Bayesian networks, Neural networks, Support vector Machine, Association rule, K-NN, CART etc. Recently, there exist various soft computing techniques for the medical diagnosis like Genetic Algorithm, Ant Colony Optimization, Firefly Algorithm, Cuckoo Search, Artificial Bee Colony, Levy Flight etc. They are also combined with the various other techniques like rough set, fuzzy logic and neural network etc. This paper presents an extensive review of literature on various hybrid technologies used for medical diagnosis.
关键词：Decision tree; Metaheutistics; Association ; Rule; Artificial Neural Network; Rough set; Fuzzy Logic ; System; SVM