Alpha---Beta bidirectional associative memories: theory and applications
Neural Processing Letters
Exact parameter determination for Parkinson's disease diagnosis with PET using an algebraic approach
AB'07 Proceedings of the 2nd international conference on Algebraic biology
SVM classification to distinguish Parkinson disease patients
Proceedings of the 1st Amrita ACM-W Celebration on Women in Computing in India
Decision support system for the diagnosis of parkinson's disease
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Morphological associative memories
IEEE Transactions on Neural Networks
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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%.