AIoT-based embedded systems optimization using feature selection for Parkinson's disease diagnosis through speech disorders

This publication has 27 references indexed in Scilit:

• A novel hybrid CNN-KNN ensemble voting classifier for Parkinson’s disease prediction from hand sketching images
  Multimedia Tools and Applications, 2024
• Predicting patients with Parkinson's disease using Machine Learning and ensemble voting technique
  Multimedia Tools and Applications, 2023
• Advancements in computer-assisted diagnosis of Alzheimer's disease: A comprehensive survey of neuroimaging methods and AI techniques for early detection
  Ageing Research Reviews, 2023
• Urine biomarkers discovery by metabolomics and machine learning for Parkinson's disease diagnoses
  Chinese Chemical Letters, 2023
• EEG analysis of Parkinson's disease using time–frequency analysis and deep learning
  Biomedical Signal Processing and Control, 2022
• Deep dual-side learning ensemble model for Parkinson speech recognition
  Biomedical Signal Processing and Control, 2021
• Insight into an unsupervised two-step sparse transfer learning algorithm for speech diagnosis of Parkinson’s disease
  Neural Computing and Applications, 2021
• Estimation of Parkinson’s disease severity using speech features and extreme gradient boosting
  Medical & Biological Engineering & Computing, 2020
• Automatic Parkinson disease detection at early stages as a pre-diagnosis tool by using classifiers and a small set of vocal features
  Biocybernetics and Biomedical Engineering, 2020
• A comparative analysis of speech signal processing algorithms for Parkinson’s disease classification and the use of the tunable Q-factor wavelet transform
  Applied Soft Computing, 2019