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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:

Deep Learning Identifies Digital Biomarkers for Self-Reported Parkinson's Disease
Hanrui Zhang, Kaiwen Deng, Hongyang Li, et al.
Patterns (2020) Vol. 1, Iss. 3, pp. 100042-100042
Open Access | Times Cited: 64

Showing 1-25 of 64 citing articles:

New era of artificial intelligence and machine learning-based detection, diagnosis, and therapeutics in Parkinson’s disease
Rohan Gupta, Smita Kumari, Anusha Senapati, et al.
Ageing Research Reviews (2023) Vol. 90, pp. 102013-102013
Closed Access | Times Cited: 54
Hybrid CNN-LSTM model with efficient hyperparameter tuning for prediction of Parkinson’s disease
Umesh Kumar Lilhore, Surjeet Dalal, Neetu Faujdar, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 42
Translational precision medicine: an industry perspective
Dominik Hartl, Valéria De Luca, Anna Kostikova, et al.
Journal of Translational Medicine (2021) Vol. 19, Iss. 1
Open Access | Times Cited: 95
Application of Deep Learning Models for Automated Identification of Parkinson’s Disease: A Review (2011–2021)
Hui Wen Loh, Wanrong Hong, Chui Ping Ooi, et al.
Sensors (2021) Vol. 21, Iss. 21, pp. 7034-7034
Open Access | Times Cited: 80
Internet of Things Technologies and Machine Learning Methods for Parkinson’s Disease Diagnosis, Monitoring and Management: A Systematic Review
Κωνσταντίνα-Μαρία Γιαννακοπούλου, Ioanna Roussaki, Konstantinos Demestichas
Sensors (2022) Vol. 22, Iss. 5, pp. 1799-1799
Open Access | Times Cited: 69
A Survey of Human Gait-Based Artificial Intelligence Applications
Elsa J. Harris, I‐Hung Khoo, Emel Demircan
Frontiers in Robotics and AI (2022) Vol. 8
Open Access | Times Cited: 67
Detection and assessment of Parkinson's disease based on gait analysis: A survey
Yao Guo, Jianxin Yang, Yuxuan Liu, et al.
Frontiers in Aging Neuroscience (2022) Vol. 14
Open Access | Times Cited: 41
Machine learning for adaptive deep brain stimulation in Parkinson’s disease: closing the loop
Andreia Oliveira, Luís Coelho, Eduardo Carvalho, et al.
Journal of Neurology (2023) Vol. 270, Iss. 11, pp. 5313-5326
Open Access | Times Cited: 29
The rise of Parkinson’s disease is a global challenge, but efforts to tackle this must begin at a national level: a protocol for national digital screening and “eat, move, sleep” lifestyle interventions to prevent or slow the rise of non-communicable diseases in Thailand
Roongroj Bhidayasiri, Jirada Sringean, Saisamorn Phumphid, et al.
Frontiers in Neurology (2024) Vol. 15
Open Access | Times Cited: 9
Progress and trends in neurological disorders research based on deep learning
Muhammad Shahid Iqbal, Md Belal Bin Heyat, Saba Parveen, et al.
Computerized Medical Imaging and Graphics (2024) Vol. 116, pp. 102400-102400
Closed Access | Times Cited: 9
A survey of deep learning techniques based Parkinson’s disease recognition methods employing clinical data
Amin Ul Haq, Jianping Li, Bless Lord Y. Agbley, et al.
Expert Systems with Applications (2022) Vol. 208, pp. 118045-118045
Closed Access | Times Cited: 34
FastEval Parkinsonism: an instant deep learning–assisted video-based online system for Parkinsonian motor symptom evaluation
Yu-Yuan Yang, Ming-Yang Ho, Chung-Hwei Tai, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 6
Reproducible Analysis Pipeline for Data Streams: Open-Source Software to Process Data Collected With Mobile Devices
Julio Vega, Meng Li, Kwesi Aguillera, et al.
Frontiers in Digital Health (2021) Vol. 3
Open Access | Times Cited: 35
Recent use of deep learning techniques in clinical applications based on gait: a survey
Yume Matsushita, Dinh Tuan Tran, Hirotake Yamazoe, et al.
Journal of Computational Design and Engineering (2021) Vol. 8, Iss. 6, pp. 1499-1532
Open Access | Times Cited: 33
Parkinson’s disease diagnosis using neural networks: Survey and comprehensive evaluation
M. Tanveer, Ashraf Haroon Rashid, Rahul Kumar, et al.
Information Processing & Management (2022) Vol. 59, Iss. 3, pp. 102909-102909
Closed Access | Times Cited: 26
Heterogeneous digital biomarker integration out-performs patient self-reports in predicting Parkinson’s disease
Kaiwen Deng, Yueming Li, Hanrui Zhang, et al.
Communications Biology (2022) Vol. 5, Iss. 1
Open Access | Times Cited: 24
Wearable sensors and features for diagnosis of neurodegenerative diseases: A systematic review
Huan Zhao, Junyi Cao, Junxiao Xie, et al.
Digital Health (2023) Vol. 9
Open Access | Times Cited: 15
BiLSTM with Data Augmentation using Interpolation Methods to Improve Early Detection of Parkinson Disease
Robertas Damaševičius, Olusola Abayomi‐Alli, Rytis Maskeliūnas, et al.
Annals of Computer Science and Information Systems (2020) Vol. 21, pp. 371-380
Open Access | Times Cited: 34
Automatic detection of Parkinson’s disease from power spectral density of electroencephalography (EEG) signals using deep learning model
Hanife Göker
Physical and Engineering Sciences in Medicine (2023) Vol. 46, Iss. 3, pp. 1163-1174
Closed Access | Times Cited: 11
Simplification of Mobility Tests and Data Processing to Increase Applicability of Wearable Sensors as Diagnostic Tools for Parkinson’s Disease
Rana M. Khalil, Lisa Shulman, Ann L. Gruber‐Baldini, et al.
Sensors (2024) Vol. 24, Iss. 15, pp. 4983-4983
Open Access | Times Cited: 4
A survey of artificial intelligence in gait-based neurodegenerative disease diagnosis
Haocong Rao, Minlin Zeng, Xuejiao Zhao, et al.
Neurocomputing (2025), pp. 129533-129533
Closed Access
Will Health Experts Adopt a Clinical Decision Support System for Game-Based Digital Biomarkers? Investigating the Impact of Different Explanations on Perceived Ease-of-Use, Perceived Usefulness, and Trust
Yu Chen, Katrien Verbert, Kathrin Gerling, et al.
(2025), pp. 1581-1597
Closed Access
Neuromechanical Biomarkers for Robotic Neurorehabilitation
Florencia Garro, Michela Chiappalone, Stefano Buccelli, et al.
Frontiers in Neurorobotics (2021) Vol. 15
Open Access | Times Cited: 27
Exploiting real-world data to monitor physical activity in patients with osteoarthritis: the opportunity of digital epidemiology
Silvia Ravalli, Federico Roggio, Giovanni Lauretta, et al.
Heliyon (2022) Vol. 8, Iss. 2, pp. e08991-e08991
Open Access | Times Cited: 17
Transformer-based transfer learning on self-reported voice recordings for Parkinson’s disease diagnosis
Ilias Tougui, Mehdi Zakroum, Ouassim Karrakchou, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
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