Associative Memory Approach for the Diagnosis of Parkinson’s Disease
Identifieur interne : 000391 ( Main/Exploration ); précédent : 000390; suivant : 000392Associative Memory Approach for the Diagnosis of Parkinson’s Disease
Auteurs : Elena Acevedo [Mexique] ; Antonio Acevedo [Mexique] ; Federico Felipe [Mexique]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2011.
Abstract
Abstract: A method for diagnosing Parkinson’s disease is presented. The proposal is based on associative approach, and we used this method for classifying patients with Parkinson’s disease and those who are completely healthy. In particular, Alpha-Beta Bidirectional Associative Memory is used together with the modified Johnson-Möbius codification in order to deal with mixed noise. We use three methods for testing the performance of our method: Leave-One-Out, Hold-Out and K-fold Cross Validation and the average obtained was of 97.17%.
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DOI: 10.1007/978-3-642-21587-2_12
Affiliations:
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