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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Parkinson’s disease detection based on multi-pattern analysis and multi-scale convolutional neural networks
Lina Qiu, Jianping Li, Jiahui Pan
Frontiers in Neuroscience (2022) Vol. 16
Open Access | Times Cited: 20

Showing 20 citing articles:

Automatic and Efficient Framework for Identifying Multiple Neurological Disorders From EEG Signals
Md. Nurul Ahad Tawhid, Siuly Siuly, Kate Wang, et al.
IEEE Transactions on Technology and Society (2023) Vol. 4, Iss. 1, pp. 76-86
Closed Access | Times Cited: 38
An efficient Parkinson's disease detection framework: Leveraging time-frequency representation and AlexNet convolutional neural network
Siuly Siuly, Smith K. Khare, Enamul Kabir, et al.
Computers in Biology and Medicine (2024) Vol. 174, pp. 108462-108462
Open Access | Times Cited: 14
A Novel EEG-Based Parkinson’s Disease Detection Model Using Multiscale Convolutional Prototype Networks
Lina Qiu, Jianping Li, Liangquan Zhong, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-14
Closed Access | Times Cited: 10
Classification of Parkinson’s disease EEG signals using 2D-MDAGTS model and multi-scale fuzzy entropy
Jun Li, Xun Li, Yuefeng Mao, et al.
Biomedical Signal Processing and Control (2024) Vol. 91, pp. 105872-105872
Closed Access | Times Cited: 8
Classifying Parkinson’s Disease Using Resting State Electroencephalogram Signals and U EN -PDNet
Syed Qasim Afser Rizvi, Guojun Wang, Asif Khan, et al.
IEEE Access (2023) Vol. 11, pp. 107703-107724
Open Access | Times Cited: 12
A novel approach for Parkinson’s disease detection using Vold-Kalman order filtering and machine learning algorithms
Fatma Lati̇foğlu, Sultan Penekli, Fırat ORHANBULUCU, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 16, pp. 9297-9311
Open Access | Times Cited: 4
A Comparative Study of Machine Learning and Deep Learning Models for Automatic Parkinson’s Disease Detection from Electroencephalogram Signals
Swagota Bera, Zong Woo Geem, Young Im Cho, et al.
Diagnostics (2025) Vol. 15, Iss. 6, pp. 773-773
Open Access
Distinguishing Parkinson’s Disease with GLCM Features from the Hankelization of EEG Signals
Mehmet Fatih Karakaş, Fatma Lati̇foğlu
Diagnostics (2023) Vol. 13, Iss. 10, pp. 1769-1769
Open Access | Times Cited: 10
Exploring the application and challenges of fNIRS technology in early detection of Parkinson’s disease
Pengsheng Hui, Yu Jiang, Jie Wang, et al.
Frontiers in Aging Neuroscience (2024) Vol. 16
Open Access | Times Cited: 2
Parkinson's disease detection from EEG signal employing autoencoder and RBFNN-based hybrid deep learning framework utilizing power spectral density
Ferdaus Anam Jibon, Alif Tasbir, Md. Alamin Talukder, et al.
Digital Health (2024) Vol. 10
Open Access | Times Cited: 2
Machine Learning-Based Detection of Parkinson’s Disease From Resting-State EEG: A Multi-Center Study
Anna Kurbatskaya, Alberto Jaramillo‐Jimenez, John Fredy Ochoa Gómez, et al.
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (2023), pp. 1-4
Open Access | Times Cited: 6
A Decision Support System For Early Stage Parkinson's Diagnosis from EEG Data Using Symbolic Mutual Information and KAC Features
Neslihan Baki, Nurhan Gürsel Özmen
Sakarya University Journal of Science (2024) Vol. 28, Iss. 5, pp. 912-923
Open Access | Times Cited: 1
Artificial intelligence for brain disease diagnosis using electroencephalogram signals
Shunuo Shang, Yingqian Shi, Yajie Zhang, et al.
Journal of Zhejiang University SCIENCE B (2024) Vol. 25, Iss. 10, pp. 914-940
Closed Access | Times Cited: 1
LRE-MMF: A novel multi-modal fusion algorithm for detecting neurodegeneration in Parkinson's disease among the geriatric population
Indranath Chatterjee, Videsha Bansal
Experimental Gerontology (2024) Vol. 197, pp. 112585-112585
Open Access | Times Cited: 1
CCZO Residual GhostNet
Arogia Victor Paul M, Sharmila Shankar
International journal of electrical and computer engineering systems (2024) Vol. 15, Iss. 3, pp. 275-283
Open Access
Ensemble classifiers fed by functional connectivity during cognitive processing differentiate Parkinson’s disease even being under medication
Emine Elif Tülay
Machine Learning Science and Technology (2024) Vol. 5, Iss. 2, pp. 025001-025001
Open Access
VAMLM-PDD: Vigorous Amalgamated Machine Learning Model for Investigating Parkinson's Disease Detection
S Prabhakar, Dogeun Park, Young-Gi Ju, et al.
(2024), pp. 1-6
Closed Access
Diagnosis of Parkinson’s Disease Using Machine Learning and Deep Learning Techniques
S. Sharanyaa, M. Sambath, Arvind Ganesh, et al.
Communications in computer and information science (2024), pp. 111-123
Closed Access
An intelligent system for monitoring and predicting Parkinson’s disease: A review
Ahmed Hammed Ayyal, Sadik Kamel Gharghan, Ammar Hussein Mutlag
AIP conference proceedings (2024) Vol. 3232, pp. 020052-020052
Closed Access
Critical analysis of Parkinson’s disease detection using EEG sub-bands and gated recurrent unit
Nauman Khalid, Muhammad Ehsan
Engineering Science and Technology an International Journal (2024) Vol. 59, pp. 101855-101855
Open Access
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