Journal of Biomedical Science and Engineering

Journal of Biomedical Science and Engineering

ISSN Print: 1937-6871
ISSN Online: 1937-688X
www.scirp.org/journal/jbise
E-mail: jbise@scirp.org
"Speech Analysis for Diagnosis of Parkinson’s Disease Using Genetic Algorithm and Support Vector Machine"
written by Mohammad Shahbakhi, Danial Taheri Far, Ehsan Tahami,
published by Journal of Biomedical Science and Engineering, Vol.7 No.4, 2014
has been cited by the following article(s):
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[15] A Comparative Study of Machine Learning Models for Parkinson's Disease Detection
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[16] Graphical assessment of the internal structure of Parkinsons dataset—a case study
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[17] Early Diagnosis of Parkinson's Disease with Speech Pronunciation Features Based on XGBoost Model
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[18] Deep Learning Based Parkinson's Disease Prediction System
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[19] EEG Analysis Using Bio-Inspired Metaheuristic Approach
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[20] Comprehensive Studies on Early Detection of Parkinson's Disease Based on Acoustic Features of Speech Using Computational Intelligence
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[22] Comparative Analysis Of The Early Detection Of Parkinson's Disease
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[23] Automatic creation of a Vowel Dataset for performing Prosody Analysis in ASD screening
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[32] X-Vectors: new quantitative biomarkers for early Parkinson's disease detection from speech
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[37] Parkinson's Disease Detection by Using Feature Selection and Sparse Representation
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[38] Non-negative matrix factorization-based time-frequency feature extraction of voice signal for Parkinson's disease prediction
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[39] A review on speech processing using machine learning paradigm
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[40] Speech-based solution to Parkinson's disease management
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[41] Insight into an unsupervised two-step sparse transfer learning algorithm for speech diagnosis of Parkinson's disease
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[42] Early diagnosis of Parkinson's disease based on non-motor symptoms: a descriptive and factor analysis
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[43] ACO Feature selection and Novel Black Widow meta-heuristic Learning rate optimized CNN for Early diagnosis of Parkinson's disease
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[44] Watermarking of Electronic Patient Record in Parkinson Disease Affected Speech: A Robust and Secure Audio Hiding Technique for Smart e-healthcare Application
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[45] Clasificación de la Enfermedad de Parkinson Utilizando Senales Cardiovasculares
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[47] Sistem za podršku odlučivanju, evaluaciju i praćenje stanja pacijenata obolelih od neurodegenerativnih bolesti
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[48] PD Care: A Framework for Advance Screening of Parkinson's Patient from Vocal Dysphonia
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[49] Data Augmentation Using GAN for Parkinson's Disease Prediction
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[50] DECISION SUPPORT SYSTEM FOR ASSESSMENT OF PATIENTS WITH NEURODEGENERATIVE DISORDERS
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[51] A Two-Step Framework for Parkinson's Disease Classification: Using Multiple One-Way ANOVA on Speech Features and Decision Trees
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[52] Hyper-parameter optimization of deep learning model for prediction of Parkinson's disease
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[53] Application of adaptive back-propagation neural networks for Parkinson's disease prediction
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[54] A data science approach for reliable classification of neuro-degenerative diseases using gait patterns
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[55] Improving mobile health apps usage: a quantitative study on mPower data of Parkinson's disease
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[56] Hybrid chaotic firefly decision making model for Parkinson's disease diagnosis
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[57] A hybrid method for the diagnosis and classifying parkinson's patients based on time–frequency domain properties and K-nearest neighbor
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[58] Analysis of Parkinson's disease diagnosis using a combination of Genetic Algorithm and Recursive Feature Elimination
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[59] EVALUATION OF FAST LEARNING MACHINE FOR IDENTIFICATION OF PARKINSON DISEASE
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[60] A technical survey on various machine learning approaches for Parkinson's disease classification
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[61] Parkinson's disease diagnosis using spiral test on digital tablets
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[62] Diagnosis of Parkinson's Disorder through Speech Data using Machine Learning Algorithms
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[63] Early Diagnosos of Parkinson's Using Dimensionality Reduction Techniques
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[64] A Knowledge Base Data Mining based on Parkinson's Disease
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[65] PARKINSON'S DISEASE CLASSIFICATION BASED ON VOWEL SOUND
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[66] Parkinson's disease diagnosis using speech signal and deep residual gated recurrent neural network
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[67] Parkinson Hastalığı Tespitinde Farklı Boyutsallık İndirgeme Yöntemlerinin Karşılaştırılması
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[70] Automatic detection of Parkinson's disease based on acoustic analysis of speech
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[71] A recurrence plot-based approach for Parkinson's disease identification
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[72] Machine Learning and Similarity Network Approaches to Support Automatic Classification of Parkinson's Diseases Using Accelerometer-based Gait Analysis
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[73] Security of Electronic Patient Record using Imperceptible DCT-SVD based Audio Watermarking Technique
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[74] PDVocal: Towards Privacy-preserving Parkinson's Disease Detection using Non-speech Body Sounds
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[75] Parkinson disease prediction using intrinsic mode function based features from speech signal
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[76] Assessing Parkinson's Disease From Speech Using Fisher Vectors
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[77] A Knowledge Based Data Mining Based on Parkinson's Desease
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[78] Diagnosis of Parkinson's Disease based on Wavelet Transform and Mel Frequency Cepstral Coefficients
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[80] Diagnosis of Parkinson's Disease Using Principle Component Analysis and Deep Learning
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[81] Optimization of Features for Classification of Parkinson's Disease from Vocal Dysphonia
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[82] Discriminating Parkinson diseased and healthy people using modified MFCC filter bank approach
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[85] Using Polar Expression Features and Nonlinear Machine Learning Classifier for Automated Parkinson's Disease Screening
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[86] Investigation and development of computational models for diagnosing early stage of Parkinson's disease using SPECT images
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[87] Early Diagnosis of Parkinson's Disease Based on Voice Tremor Using Ann
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[88] Objective assessment of Parkinson's disease using machine learning
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