Multidimensional Neo-Fuzzy-Neuron for Solving Medical Diagnostics Tasks in Online-Mode
Ładowanie...
Data
2017
Tytuł czasopisma
ISSN czasopisma
Tytuł tomu
Wydawca
Wydawnictwo Politechniki Łódzkiej
Lodz University of Technology Press
Lodz University of Technology Press
Abstrakt
In this paper neuro-fuzzy approach for medical data processing is considered. Special capacities for methods and systems of Computational Intelligence were introduced for Medical Data Mining tasks, like transparency and interpretability of obtained results, ability to classify nonconvex and overlapped classes that correspond to various diagnoses, necessity to process data in online mode and so on. Architecture based on the multidimensional neo-fuzzy-neuron was designed for situation of many diagnoses. For multidimensional neo-fuzzy-neuron adaptive learning algorithms that are a modification of Widrow-Hoff algorithm were introduced. This system was approbate on nervous system diseases data set from University of California Irvine (UCI) Repository and show high level of classification results.
Opis
Słowa kluczowe
multidimensional neo-fuzzy-neuron, Medical Data Mining, computational intelligence, Parkinson disease, learning algorithm, fuzzyfication, wielowymiarowy neo-rozmyty-neuron, eksploracja danych medycznych, inteligencja obliczeniowa, choroba Parkinsona, algorytm uczenia, rozmycie
Cytowanie
Mahmoud, S. M. K., Perova, I., & Pliss, I. (2017). Multidimensional Neo-Fuzzy-Neuron for Solving Medical Diagnostics Tasks in Online-Mode. Journal of Applied Computer Science, 25(1), 39-48. https://doi.org/10.34658/jacs.2017.1.39-48