Associative Memory Approach for the Diagnosis of Parkinson’s Disease

  • Elena Acevedo
  • Antonio Acevedo
  • Federico Felipe
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6718)

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%.

Keywords

Classification Associative Models Alpha-Beta BAM Codification 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Elena Acevedo
    • 1
  • Antonio Acevedo
    • 1
  • Federico Felipe
    • 1
  1. 1.Escuela Superior de Ingeniería Mecánica y Eléctrica, IPNMexico CityMexico

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