Abstract
Parkinson’s disease is a neuro-degenerative movement disorder that causes voice and speech disorders. Therefore, the disease can be diagnosed as a dysfunctional disease. In this study, Computational Intelligence Methods, a new method for classifying Parkinson’s disease, have been used. This method has been tested with two data sets and compared with classical methods. According to the obtained results, this method yielded better results than the classical methods.
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Huseyn, E. (2019). Z-Number Based Diagnostics of Parkinson’s Diseases. In: Aliev, R., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Sadikoglu, F. (eds) 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018. ICAFS 2018. Advances in Intelligent Systems and Computing, vol 896. Springer, Cham. https://doi.org/10.1007/978-3-030-04164-9_125
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DOI: https://doi.org/10.1007/978-3-030-04164-9_125
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Online ISBN: 978-3-030-04164-9
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