Neural Networks
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Fast linear discriminant analysis using binary bases
Pattern Recognition Letters
Low-frequency vocal modulations in vowels produced by Parkinsonian subjects
Speech Communication
A new feature selection method for Gaussian mixture clustering
Pattern Recognition
A comparison of multiple classification methods for diagnosis of Parkinson disease
Expert Systems with Applications: An International Journal
Nonlinear Models Using Dirichlet Process Mixtures
The Journal of Machine Learning Research
Digital Signal Processing Using Matlab
Digital Signal Processing Using Matlab
Multiclass relevance vector machines: sparsity and accuracy
IEEE Transactions on Neural Networks
Feature selection using fuzzy entropy measures with similarity classifier
Expert Systems with Applications: An International Journal
Artificial Intelligence in Medicine
A parallel neural network approach to prediction of Parkinson's Disease
Expert Systems with Applications: An International Journal
Clustering technique-based least square support vector machine for EEG signal classification
Computer Methods and Programs in Biomedicine
Computer Methods and Programs in Biomedicine
Expert Systems with Applications: An International Journal
Pathological infant cry analysis using wavelet packet transform and probabilistic neural network
Expert Systems with Applications: An International Journal
A general regression neural network
IEEE Transactions on Neural Networks
Computer Methods and Programs in Biomedicine
Expert Systems with Applications: An International Journal
Computer Methods and Programs in Biomedicine
Computer Methods and Programs in Biomedicine
A systematic approach to embedded biomedical decision making
Computer Methods and Programs in Biomedicine
A comparative study of wavelet families for classification of wrist motions
Computers and Electrical Engineering
Computer Methods and Programs in Biomedicine
Automatic segmentation of corpus collasum using Gaussian mixture modeling and Fuzzy C means methods
Computer Methods and Programs in Biomedicine
New machine-learning algorithms for prediction of Parkinson's disease
International Journal of Systems Science
Computer Methods and Programs in Biomedicine
| Hi-index | 0.00 |
Elderly people are commonly affected by Parkinson's disease (PD) which is one of the most common neurodegenerative disorders due to the loss of dopamine-producing brain cells. People with PD's (PWP) may have difficulty in walking, talking or completing other simple tasks. Variety of medications is available to treat PD. Recently, researchers have found that voice signals recorded from the PWP is becoming a useful tool to differentiate them from healthy controls. Several dysphonia features, feature reduction/selection techniques and classification algorithms were proposed by researchers in the literature to detect PD. In this paper, hybrid intelligent system is proposed which includes feature pre-processing using Model-based clustering (Gaussian mixture model), feature reduction/selection using principal component analysis (PCA), linear discriminant analysis (LDA), sequential forward selection (SFS) and sequential backward selection (SBS), and classification using three supervised classifiers such as least-square support vector machine (LS-SVM), probabilistic neural network (PNN) and general regression neural network (GRNN). PD dataset was used from University of California-Irvine (UCI) machine learning database. The strength of the proposed method has been evaluated through several performance measures. The experimental results show that the combination of feature pre-processing, feature reduction/selection methods and classification gives a maximum classification accuracy of 100% for the Parkinson's dataset.