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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:

An automatic non-invasive method for Parkinson's disease classification
Deepak Joshi, Aayushi Khajuria, Pradeep Joshi
Computer Methods and Programs in Biomedicine (2017) Vol. 145, pp. 135-145
Closed Access | Times Cited: 116

Showing 1-25 of 116 citing articles:

Machine Learning for the Diagnosis of Parkinson's Disease: A Review of Literature
Jie Mei, Christian Desrosiers, Johannes Frasnelli
Frontiers in Aging Neuroscience (2021) Vol. 13
Open Access | Times Cited: 268
Parkinson's disease: Cause factors, measurable indicators, and early diagnosis
Shreya Bhat, U. Rajendra Acharya, Yuki Hagiwara, et al.
Computers in Biology and Medicine (2018) Vol. 102, pp. 234-241
Closed Access | Times Cited: 170
Explainable machine learning models based on multimodal time-series data for the early detection of Parkinson’s disease
Muhammad Junaid, Sajid Ali, Fatma Eid, et al.
Computer Methods and Programs in Biomedicine (2023) Vol. 234, pp. 107495-107495
Closed Access | Times Cited: 44
Artificial Intelligence Techniques for Automated Diagnosis of Neurological Disorders
U. Raghavendra, U. Rajendra Acharya, Hojjat Adeli
European Neurology (2019) Vol. 82, Iss. 1-3, pp. 41-64
Open Access | Times Cited: 131
Automated detection of Parkinson's disease using minimum average maximum tree and singular value decomposition method with vowels
Türker Tuncer, Şengül Doğan, U. Rajendra Acharya
Journal of Applied Biomedicine (2019) Vol. 40, Iss. 1, pp. 211-220
Closed Access | Times Cited: 104
Data-Driven Based Approach to Aid Parkinson’s Disease Diagnosis
Nicolas Khoury, Ferhat Attal, Yacine Amirat, et al.
Sensors (2019) Vol. 19, Iss. 2, pp. 242-242
Open Access | Times Cited: 91
Supervised machine learning based gait classification system for early detection and stage classification of Parkinson’s disease
E. Balaji, D. Brindha, Balakrishnan Ramasamy
Applied Soft Computing (2020) Vol. 94, pp. 106494-106494
Closed Access | Times Cited: 90
A Hybrid Approach to Parkinson Disease Classification Using Speech Signal: The Combination of SMOTE and Random Forests
Kemal Polat
(2019), pp. 1-3
Closed Access | Times Cited: 83
Detection of Parkinson’s disease from EEG signals using discrete wavelet transform, different entropy measures, and machine learning techniques
Majid Aljalal, Saeed A. Aldosari, Marta Molinas, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 57
Parkinson’s Disease Detection from Resting-State EEG Signals Using Common Spatial Pattern, Entropy, and Machine Learning Techniques
Majid Aljalal, Saeed A. Aldosari, Khalil AlSharabi, et al.
Diagnostics (2022) Vol. 12, Iss. 5, pp. 1033-1033
Open Access | Times Cited: 51
Parkinson’s disease diagnosis and stage prediction based on gait signal analysis using EMD and CNN–LSTM network
B. Vidya, P. Sasikumar
Engineering Applications of Artificial Intelligence (2022) Vol. 114, pp. 105099-105099
Closed Access | Times Cited: 41
Using gait analysis’ parameters to classify Parkinsonism: A data mining approach
Carlo Ricciardi, Marianna Amboni, Chiara De Santis, et al.
Computer Methods and Programs in Biomedicine (2019) Vol. 180, pp. 105033-105033
Closed Access | Times Cited: 67
Machine Learning and Similarity Network Approaches to Support Automatic Classification of Parkinson’s Diseases Using Accelerometer-based Gait Analysis
Elham Rastegari, Sasan Azizian, Hesham Ali
Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences (2019)
Open Access | Times Cited: 56
Data-driven gait analysis for diagnosis and severity rating of Parkinson’s disease
E Balaji, D. Brindha, Vinodh Kumar Elumalai, et al.
Medical Engineering & Physics (2021) Vol. 91, pp. 54-64
Closed Access | Times Cited: 49
Machine Learning Methods with Decision Forests for Parkinson’s Detection
Moumita Pramanik, Ratika Pradhan, Parvati Nandy, et al.
Applied Sciences (2021) Vol. 11, Iss. 2, pp. 581-581
Open Access | Times Cited: 44
Machine learning approach for classification of Parkinson disease using acoustic features
Vikas Mittal, R. K. Sharma
Journal of Reliable Intelligent Environments (2021) Vol. 7, Iss. 3, pp. 233-239
Closed Access | Times Cited: 42
Role of Wearable Sensors with Machine Learning Approaches in Gait Analysis for Parkinson's Disease Assessment: A Review
Aishwarya Balakrishnan, Jeevan Medikonda, Pramod K. Namboothiri, et al.
Engineered Science (2022)
Open Access | Times Cited: 36
NDDNet: a deep learning model for predicting neurodegenerative diseases from gait pattern
Md. Ahasan Atick Faisal, Muhammad E. H. Chowdhury, Zaid Bin Mahbub, et al.
Applied Intelligence (2023) Vol. 53, Iss. 17, pp. 20034-20046
Closed Access | Times Cited: 16
Classification of Parkinson’s disease EEG signals using 2D-MDAGTS model and multi-scale fuzzy entropy
J. H. Li, Xun Li, Yuefeng Mao, et al.
Biomedical Signal Processing and Control (2024) Vol. 91, pp. 105872-105872
Closed Access | Times Cited: 7
Classification of gait patterns between patients with Parkinson’s disease and healthy controls using phase space reconstruction (PSR), empirical mode decomposition (EMD) and neural networks
Wei Zeng, Chengzhi Yuan, Qinghui Wang, et al.
Neural Networks (2019) Vol. 111, pp. 64-76
Closed Access | Times Cited: 53
An improved sex-specific and age-dependent classification model for Parkinson's diagnosis using handwriting measurement
Ujjwal Gupta, Hritik Bansal, Deepak Joshi
Computer Methods and Programs in Biomedicine (2019) Vol. 189, pp. 105305-105305
Open Access | Times Cited: 51
A robust, cost-effective and non-invasive computer-aided method for diagnosis three types of neurodegenerative diseases with gait signal analysis
Seyede Marziyeh Ghoreshi Beyrami, Peyvand Ghaderyan
Measurement (2020) Vol. 156, pp. 107579-107579
Closed Access | Times Cited: 43
Parkinson disease classification using one against all based data sampling with the acoustic features from the speech signals
Kemal Polat, Majid Nour
Medical Hypotheses (2020) Vol. 140, pp. 109678-109678
Closed Access | Times Cited: 43
Classification of Parkinson Disease Based on Patient’s Voice Signal Using Machine Learning
Imran Ahmed, Sultan Aljahdali, Muhammad Shakeel Khan, et al.
Intelligent Automation & Soft Computing (2021) Vol. 32, Iss. 2, pp. 705-722
Open Access | Times Cited: 32
A Systematic Review of Time Series Classification Techniques Used in Biomedical Applications
Will Ke Wang, I.-Yuan Chen, Leeor Hershkovich, et al.
Sensors (2022) Vol. 22, Iss. 20, pp. 8016-8016
Open Access | Times Cited: 27
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