A Spectrogram-Based Deep Feature Assisted Computer-Aided Diagnostic System for Parkinson’s Disease

Author:

Zahid LaibaORCID,Maqsood MuazzamORCID,Durrani Mehr Yahya,Bakhtyar Maheen,Baber Junaid,Jamal Habibullah,Mehmood Irfan,Song Oh-YoungORCID

Funder

MSIT (Ministry of Science and ICT), South Korea, through the Information Technology Research Center (ITRC) Support Program

Institute for Information & Communications Technology Planning & Evaluation

Sejong University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Cited by 53 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A hybrid approach to detecting Parkinson's disease using spectrogram and deep learning CNN-LSTM network;International Journal of Speech Technology;2024-07-18

2. Vision Transformer Based Classification of Neurological Disorders from Human Speech;Firat University Journal of Experimental and Computational Engineering;2024-06-12

3. Early Parkinson's Disease Diagnosis Using Multi-Modal CASENet CNN-LSTM;Advances in Healthcare Information Systems and Administration;2024-05-17

4. BEiT Transformer Models to Aid in the Early Detection of Parkinson Illness;2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI);2024-05-09

5. Parkinson’s Disease Detection: VGG-ResNet Hybrid Approach;2024 10th International Conference on Communication and Signal Processing (ICCSP);2024-04-12

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