Classifying Parkinson’s Disease Using Resting State Electroencephalogram Signals and U<sup> <i>EN</i> </sup>-PDNet-Reference-Cited by-同舟云学术

Classifying Parkinson’s Disease Using Resting State Electroencephalogram Signals and U^EN-PDNet

Author:

Rizvi Syed Qasim Afser¹^ORCID,Wang Guojun¹^ORCID,Khan Asif²^ORCID,Hasan Mohammad Kamrul³^ORCID,Ghazal Taher M.³^ORCID,Khan Atta Ur Rehman⁴^ORCID

Affiliation:

1. School of Computer Science, Guangzhou University, Guangzhou, China

2. Department of Computer Application, Integral University, Lucknow, Uttar Pradesh, India

3. Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Malaysia

4. College of Engineering and IT, Ajman University, Ajman, United Arab Emirates

Funder

National Natural Science Foundation of China

Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference46 articles.

2. UC San Diego resting state EEG data from patients with Parkinson’s disease;rockhill,2020

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5. Machine Learning based Early Detection and Monitoring of Parkinson Disease;2023 9th International Conference on Smart Structures and Systems (ICSSS);2023-11-23