The identification and clustering analysis of auditory neurons for salicylated-induced rat model

Kuo Sheng Cheng, Li Hui Chen, Yi Jung Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Salicylate-induced rat model is one of the animal models for tinnitus study. In this study, a radial basis function neural network for automatic identification is firstly developed due to its features of easy training and learning. From the experimental results, the recognition rate is demonstrated to be as high as 98%. Not only the recognition rate is improved, but also it is very objective in analysis. Secondly, a support vector clustering is applied to neurons distribution analysis. Based on the clustering analysis, it is found that the cluster number and distribution area for the Salicylated-induced fos-labeled neurons are very different from those of controlled group.

Original languageEnglish
Title of host publicationProceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Pages6281-6284
Number of pages4
Publication statusPublished - 2005 Dec 1
Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
Duration: 2005 Sep 12005 Sep 4

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume7 VOLS
ISSN (Print)0589-1019

Other

Other2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Country/TerritoryChina
CityShanghai
Period05-09-0105-09-04

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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