文章基本信息

标题：Use of Fuzzy C-Mean and Fuzzy Min-Max Neural Network in Lung Cancer Detection
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作者：Kiran S. Darne ; Suja S. Panicker
期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2013
卷号：3
期号：3
页码：265-269
出版社：International Journal of Soft Computing & Engineering
摘要：Lung cancer is a disease characterized by uncontrolled cell growth in tissues of the lung and is the most common fatal malignancy in both men and women. Early detection and treatment of lung cancer can greatly improve the survival rate of patient. Artificial Neural Network (ANN), Fuzzy C-Mean (FcM) and Fuzzy Min-Max Neural network (FMNN) are useful in medical diagnosis because of several advantages. Like ANN has fault tolerance, flexibility, non linearity, while FcM gives best result for overlapped data set, data point may belong to more then one cluster center and always converges .and , also, FMNN has advantages like online adaptation, non-linear separability, less training time, soft and hard decision. In this work, we propose to use FcM and FMNN on standard datasets, to detect lung cancer
关键词：Classification; Clustering; Fuzzy System; FCM;FMNN.