A Comparative Study of Machine Learning Models for Parkinson’s Disease Detection

Author:

Bunterngchit Chayut1,Bunterngchit Yuthachai2

Affiliation:

1. Chinese Academy of Sciences,State Key Laboratory of Management and Control for Complex Systems, Institute of Automation,Beijing,China

2. Siam University,Graduate School of Engineering,Bangkok,Thailand

Publisher

IEEE

Reference28 articles.

1. Breast Cancer Prediction via Machine Learning

2. Skin Cancer Classification using Deep Learning and Transfer Learning

3. Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques;mohan;IEEE Access,2019

4. Parkinson’s Disease Diagnosis Using Machine Learning and Voice;wroge;2018 IEEE Signal Processing in Medicine and Biology Symposium (SPMB),2018

5. A Comparative Study of Parkinson Disease Diagnosis in Machine Learning;thanoun;2020 The 4th International Conference on Advances in Artificial Intelligence,2020

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1. Detection of Parkinson's Disease using Machine Learning Algorithms from Speech Signals;2024 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT);2024-07-04

2. An Adaptive Intelligent Polar Bear (AIPB) Optimization-Quantized Contempo Neural Network (QCNN) model for Parkinson’s disease diagnosis using speech dataset;Biomedical Signal Processing and Control;2024-01

3. Enhanced EEG-fNIRS Classification through Concatenated Convolutional Neural Network with Band Analysis;2023 IEEE International Conference on Robotics and Biomimetics (ROBIO);2023-12-04

4. Review of Metaheuristic Algorithms in Feature Selection based on Parkinson Disease;2023 24th International Conference on Control Systems and Computer Science (CSCS);2023-05

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