@inproceedings{91e7104026d04765847d3d5b3e074221,
title = "A novel and efficient neuro-fuzzy classifier for medical diagnosis",
abstract = "This study attempts to propose a novel neuro-fuzzy network which can efficiently reason fuzzy rules based on training data to solve the medical diagnosis problems. First, this study proposes a refined K-means clustering algorithm and a gradient-based learning rules to logically determine and adaptively tuned the fuzzy membership functions for the employed neuro-fuzzy network. In the meanwhile, this study also presents a feature reduction scheme based on the grey-relational analysis to simplify the fuzzy rules obtained from the employed neuro-fuzzy network. Experimental results indicated that the proposed neuro-fuzzy network with feature reduction can discover very simplified and easily interpretable fuzzy rules to support medical diagnosis.",
author = "Hong, \{Chin Ming\} and Chen, \{Chih Ming\} and Chen, \{Shyuan Yi\} and Huang, \{Chao Yen\}",
year = "2006",
language = "English",
isbn = "0780394909",
series = "IEEE International Conference on Neural Networks - Conference Proceedings",
pages = "735--741",
booktitle = "International Joint Conference on Neural Networks 2006, IJCNN '06",
note = "International Joint Conference on Neural Networks 2006, IJCNN '06 ; Conference date: 16-07-2006 Through 21-07-2006",
}