Parkinson’s detection based on combined CNN and LSTM using enhanced speech signals with Variational mode decomposition

This publication has 30 references indexed in Scilit:

• Feature-driven machine learning to improve early diagnosis of Parkinson's disease
  Expert Systems with Applications, 2018
• Analysis and Classification of Cold Speech Using Variational Mode Decomposition
  IEEE Transactions on Affective Computing, 2017
• A two-stage variable selection and classification approach for Parkinson’s disease detection by using voice recording replications
  Computer Methods and Programs in Biomedicine, 2017
• Speech enhancement based on mEMD‐VMD method
  Electronics Letters, 2017
• Optimizing diagnosis in Parkinson's disease: Radionuclide imaging
  Parkinsonism & Related Disorders, 2016
• Detecting Patients with Parkin son’s disease using Mel Frequency Cepstral Coefficients a nd Support Vector Machines
  International Journal on Electrical Engineering and Informatics, 2015
• Ageing and Parkinson's disease: Why is advancing age the biggest risk factor?
  Ageing Research Reviews, 2014
• Variational Mode Decomposition
  IEEE Transactions on Signal Processing, 2013
• Collection and Analysis of a Parkinson Speech Dataset With Multiple Types of Sound Recordings
  IEEE Journal of Biomedical and Health Informatics, 2013
• SVM classification to distinguish Parkinson disease patients
  2010