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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:

Early diagnosis of Parkinson's disease using Continuous Convolution Network: Handwriting recognition based on off-line hand drawing without template
Zhu Li, Jiayu Yang, Yanwen Wang, et al.
Journal of Biomedical Informatics (2022) Vol. 130, pp. 104085-104085
Open Access | Times Cited: 25

Showing 25 citing articles:

Parkinson’s disease diagnosis using deep learning: A bibliometric analysis and literature review
Rabab Ali Abumalloh, Mehrbakhsh Nilashi, Sarminah Samad, et al.
Ageing Research Reviews (2024) Vol. 96, pp. 102285-102285
Closed Access | Times Cited: 11
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
A three-stage fuzzy classifier method for Parkinson’s disease diagnosis using dynamic handwriting analysis
Konstantin Sarin, Marina Bardamova, Mikhail Svetlakov, et al.
Decision Analytics Journal (2023) Vol. 8, pp. 100274-100274
Open Access | Times Cited: 11
ChiGa-Net: A genetically optimized neural network with refined deeply extracted features using χ2 statistical score for trustworthy Parkinson’s disease detection
Liaqat Ali, Man-Fai Leung, Muhammad Asghar Khan, et al.
Neurocomputing (2025), pp. 129450-129450
Closed Access
Towards Parkinson’s Disease Detection Through Analysis of Everyday Handwriting
J. D. Gallo-Aristizabal, Daniel Escobar-Grisales, Cristian David Ríos-Urrego, et al.
Diagnostics (2025) Vol. 15, Iss. 3, pp. 381-381
Open Access
Deep Learning-Based Diagnostic Model for Parkinson's Disease Using Handwritten Spiral and Wave Images
K. Aditya Shastry
Current Medical Science (2025)
Closed Access
A new network structure for Parkinson's handwriting image recognition
Jiang Xiao, Haibin Yu, Jiayu Yang, et al.
Medical Engineering & Physics (2025), pp. 104333-104333
Closed Access
A Parkinson's Auxiliary Diagnosis Algorithm Based on a Hyperparameter Optimization Method of Deep Learning
Xingbo Wang, Shujuan Li, Chi‐Man Pun, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2023) Vol. 21, Iss. 4, pp. 912-923
Closed Access | Times Cited: 10
Deep Learning–Based Artificial Intelligence Algorithm to Classify Tremors from Hand‐Drawn Spirals
Reghu Anandapadmanabhan, Aayushi Vishnoi, Geetha Raman, et al.
Movement Disorders (2025)
Closed Access
Automatic diagnosis of multi-task in essential tremor: Dynamic handwriting analysis using multi-modal fusion neural network
Chenbin Ma, Yu‐Lan Ma, Longsheng Pan, et al.
Future Generation Computer Systems (2023) Vol. 145, pp. 429-441
Closed Access | Times Cited: 7
An Overview of Hand-Drawn Diagram Recognition Methods and Applications
Vanita Agrawal, Jayant Jagtap, MVV Prasad Kantipudi
IEEE Access (2024) Vol. 12, pp. 19739-19751
Open Access | Times Cited: 2
ILSHIP: An interpretable and predictive model for hypothyroidism
Bin Liao, Jinming Liang, Binglei Guo, et al.
Computers in Biology and Medicine (2023) Vol. 154, pp. 106578-106578
Closed Access | Times Cited: 4
Early diagnosis of Parkinson disorder based on spiral drawing image modalities using hybrid transfer learning architecture
C.D. Anisha, N. Arulanand
Journal of Intelligent & Fuzzy Systems (2024) Vol. 46, Iss. 1, pp. 769-787
Closed Access | Times Cited: 1
Parkinson’s Disease Detection from Voice Recordings Using Associative Memories
Irving Luna-Ortiz, Mario Aldape-Pérez, Abril Valeria Uriarte-Arcia, et al.
Healthcare (2023) Vol. 11, Iss. 11, pp. 1601-1601
Open Access | Times Cited: 3
A Transfer Learning Approach with MobileNetV2 for Parkinson’s Disease Detection using Hand-Drawings
B. Anil Kumar, Mohan Bansal
2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT) (2023), pp. 1-7
Closed Access | Times Cited: 2
Parkinson’s disease detection using a novel weighted ensemble of CNN models
Harshvardhan Rai, Abhishek Bajpai, Mohini Tyagi, et al.
2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT) (2023), pp. 1-6
Closed Access | Times Cited: 2
ParTRE: A relational triple extraction model of complicated entities and imbalanced relations in Parkinson’s disease
Xiaoming Zhang, Can Yu, Rui Yan
Journal of Biomedical Informatics (2024) Vol. 152, pp. 104624-104624
Closed Access
Enhancing Parkinson's Disease Recognition through Multimodal Analysis of Archimedean Spiral Drawings
Attila Zoltán Jenei, Dávid Sztahó, István Valálik
Híradástechnika/Infocommunications journal (2024) Vol. 16, Iss. 1, pp. 64-71
Open Access
Mobilenet-V2 Enhanced Parkinson's Disease Prediction with Hybrid Data Integration
Sameer Ahmad Bhat, Piotr Szczuko
Proceedings of the International Conference on Information Systems Development (2024)
Closed Access
Enhancing Parkinson’s Disease Detection Through Handwriting Analysis: A Deep Learning Approach with Segmentation and Transfer Learning
S.M. Rhydh Arnab, Mohammad Rakin Uddin, Atik Jawad
(2023), pp. 1-5
Closed Access | Times Cited: 1
An Offline Handwriting Age Range Prediction System Using an Optimized Deep Learning Technique
Olusanya Olamide Omolara, Mayowa O. Oyediran, Elegbede Adedayo Wasiat, et al.
International Journal of Emerging Technology and Advanced Engineering (2023) Vol. 13, Iss. 4, pp. 105-115
Open Access
Inteligencia artificial en la enfermedad de Parkinson y otros trastornos del movimiento
José Lapeña Motilva, Álvaro Sánchez‐Ferro
Kranion (2023) Vol. 18, Iss. 2
Open Access
Machine Learning Applications that Might Support Home-Based Screening of Parkinson’s Disease: A Scoping Review
Catarina Abreu, Gonçalo Ferrão da Costa, João Tiago Oliveira, et al.
Lecture notes in networks and systems (2023), pp. 431-442
Closed Access
Fuzzy Classifiers for Diagnosing of Parkinson’s Disease Based on Static Handwritten Data
Ilya Hodashinsky, Yu. A. Shurygin, Konstantin Sarin, et al.
Optoelectronics Instrumentation and Data Processing (2023) Vol. 59, Iss. 3, pp. 346-357
Closed Access
Teaching Pattern of Disease Diagnosis and Treatment Technology Curriculum Based on Internet
Haiyang Wang, Cuiqing Zhao, Linming Liu, et al.
(2022), pp. 1-6
Closed Access
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