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Implementation on the Classifier for Differential Diagnosis of Laryngeal Disease using Hierarchical Neural Network  

김경태 (부산대학교 의공학과)
김길중 (동서대학교 전자공학과)
전계록 (부산대학교 의과대학 의공학교실)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.6, no.1, 2002 , pp. 76-82 More about this Journal
Abstract
In this paper, we implemented on the classifier for differential diagnosis of laryngeals disease which is normal, polyp, nodule, palsy, and each step of glottic cancer using hierarchical neural network. We conducted on classifier of various vowels as /a/, /e/, /i/, /o/, /u/ from normal group, laryngeal disease group, each step of cancer group. The experimental result on classification of each vowels as follows. A /a/ vowel shows excellent classification result to the other vowels in regard to each Input parameters. Thus we implemented the hierarchical neural network for differential diagnosis of laryngeals disease using only /a/ vowel. A implemented hierarchical neural network is composed of each other laryngeals disease apply to each other parameter in each hierarchical layer. We take the voice signals from patient who get the laryngeal disease and glottic cancer, and then use the APQ, PPQ, vAm, Jitter, Shimmer, RAP as input parameter of neural networks.
Keywords
hierarchical neural network; glottic cancer; laryngeal disease;
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