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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:

Dysphonic Voice Pattern Analysis of Patients in Parkinson’s Disease Using Minimum Interclass Probability Risk Feature Selection and Bagging Ensemble Learning Methods
Yunfeng Wu, Pinnan Chen, Yuchen Yao, et al.
Computational and Mathematical Methods in Medicine (2017) Vol. 2017, pp. 1-11
Open Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare
Polina Mamoshina, Lucy O. Ojomoko, Yury Yanovich, et al.
Oncotarget (2017) Vol. 9, Iss. 5, pp. 5665-5690
Open Access | Times Cited: 411
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
Imperative Role of Machine Learning Algorithm for Detection of Parkinson’s Disease: Review, Challenges and Recommendations
Arti Rana, Ankur Dumka, Rajesh Singh, et al.
Diagnostics (2022) Vol. 12, Iss. 8, pp. 2003-2003
Open Access | Times Cited: 65
Speech Based Estimation of Parkinson’s Disease Using Gaussian Processes and Automatic Relevance Determination
Vladimir Despotović, Tomáš Škovránek, Christoph Schommer
Neurocomputing (2020) Vol. 401, pp. 173-181
Closed Access | Times Cited: 51
Using Machine Learning to Predict the Sentiment of Online Reviews: A New Framework for Comparative Analysis
Gregorius Satia Budhi, Raymond Chiong, Ilung Pranata, et al.
Archives of Computational Methods in Engineering (2021) Vol. 28, Iss. 4, pp. 2543-2566
Closed Access | Times Cited: 45
Enhanced decision tree induction using evolutionary techniques for Parkinson's disease classification
Mostafa Ghane, Mei Choo Ang, Mehrbakhsh Nilashi, et al.
Journal of Applied Biomedicine (2022) Vol. 42, Iss. 3, pp. 902-920
Closed Access | Times Cited: 27
A Novel Framework of Two Successive Feature Selection Levels Using Weight-Based Procedure for Voice-Loss Detection in Parkinson’s Disease
Amira S. Ashour, Majid Nour, Kemal Polat, et al.
IEEE Access (2020) Vol. 8, pp. 76193-76203
Open Access | Times Cited: 31
AutoHealth: Advanced LLM-Empowered Wearable Personalized Medical Butler for Parkinson’s Disease Management
Luis Cardenas, Katherine Parajes, Ming Zhu, et al.
2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC) (2024), pp. 0375-0379
Closed Access | Times Cited: 2
Simple Logistic Hybrid System Based on Greedy Stepwise Algorithm for Feature Analysis to Diagnose Parkinson’s Disease According to Gender
Şule Yücelbaş
Arabian Journal for Science and Engineering (2020) Vol. 45, Iss. 3, pp. 2001-2016
Closed Access | Times Cited: 17
The Current State and Future Possibilities of Mobile Phone “Voice Analyser” Applications, in Relation to Otorhinolaryngology
Amberley Jade Munnings
Journal of Voice (2019) Vol. 34, Iss. 4, pp. 527-532
Closed Access | Times Cited: 17
Classification of Dysphonic Voices in Parkinson’s Disease with Semi-Supervised Competitive Learning Algorithm
Guidong Bao, Meng-Chen Lin, Xiaoqian Sang, et al.
Biosensors (2022) Vol. 12, Iss. 7, pp. 502-502
Open Access | Times Cited: 9
Early diagnosis of Parkinson’s disease using a hybrid method of least squares support vector regression and fuzzy clustering
Hossein Ahmadi, Lin Huo, Goli Arji, et al.
Journal of Applied Biomedicine (2024) Vol. 44, Iss. 3, pp. 569-585
Open Access | Times Cited: 1
A Computational Method for the Identification of Endolysins and Autolysins
Lei Xu, Guangmin Liang, Baowen Chen, et al.
Protein and Peptide Letters (2019) Vol. 27, Iss. 4, pp. 329-336
Closed Access | Times Cited: 11
Early Prediction of Parkinson's Disease (PD) Using Ensemble Classifiers
Anisha C. D, N. Arulanand
(2020)
Closed Access | Times Cited: 11
The effect of a prolonged and demanding vocal activity (Divya Prabhandam recitation) on subjective and objective measures of voice among Indian Hindu priests
S. Y. Aishwarya, Srirangam Vijayakumar Narasimhan
Speech Language and Hearing (2021) Vol. 25, Iss. 4, pp. 498-506
Closed Access | Times Cited: 8
How does noise pollution exposure affect vocal behavior? A systematic review
Eugenia I. Toki, Polyxeni Fakitsa, Konstantinos Plachouras, et al.
AIMS Medical Science (2021) Vol. 8, Iss. 2, pp. 116-137
Open Access | Times Cited: 7
Outlier Detection Using Improved Support Vector Data Description in Wireless Sensor Networks
Pei Shi, Guanghui Li, Yuan Yongming, et al.
Sensors (2019) Vol. 19, Iss. 21, pp. 4712-4712
Open Access | Times Cited: 6
Comparing Support Vector Machine and Naïve Bayes Methods with A Selection of Fast Correlation Based Filter Features in Detecting Parkinson's Disease
Yuniar Farida, Nurissaidah Ulinnuha, Silvia Kartika Sari, et al.
Lontar Komputer Jurnal Ilmiah Teknologi Informasi (2023) Vol. 14, Iss. 2, pp. 80-80
Open Access | Times Cited: 2
DFS-WR: A novel dual feature selection and weighting representation framework for classification
Zhimin Zhang, Fan Zhang, Ling‐Feng Mao, et al.
Information Fusion (2023) Vol. 104, pp. 102191-102191
Closed Access | Times Cited: 2
Diagnosing Parkinson’s Disease: its evolution to future
Richa Indu, Sushil Chandra Dimri
2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) (2022), pp. 108-115
Closed Access | Times Cited: 4
Detection of Parkinson’s Disease (PD) Based On Speech Recordings using Machine Learning Techniques
Azian Azamimi Abdullah, Nurul Nurain Norazman, Wan Khairunizam, et al.
2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) (2020) Vol. 19, pp. 1-6
Closed Access | Times Cited: 4
Demystifying Machine Learning Predictions: A Comparative Analysis with Explainable AI for Parkinson's Disease
S. Jayanthi, K. M. Abubakkar Sithik, U Balashivudu U
Research Square (Research Square) (2024)
Open Access
Correlation-Based Weight Algorithm for Diagnosing Parkinson’s Induced Voice Disorder
Richa Indu, Sushil Chandra Dimri
SN Computer Science (2024) Vol. 5, Iss. 7
Closed Access
Machine Learning Based Parkinson’s Disease Detection Using Voice and Handwriting Analysis
Sauransh Singh, Ruchir Kumar Kadwey, S. Krishna Srivatsava, et al.
Transactions on computer systems and networks (2024), pp. 171-186
Closed Access
Parkinson's Disease Detection Using Voice and Speech—Systematic Literature Review
Ronak Khatwad, Suyash Tiwari, Yash Tripathi, et al.
(2024), pp. 41-74
Closed Access
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