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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:

Feature-driven machine learning to improve early diagnosis of Parkinson's disease
Luca Parisi, Narrendar RaviChandran, Marianne Lyne Manaog
Expert Systems with Applications (2018) Vol. 110, pp. 182-190
Closed Access | Times Cited: 147

Showing 1-25 of 147 citing articles:

Deep Learning-Based Parkinson’s Disease Classification Using Vocal Feature Sets
Hakan Gündüz
IEEE Access (2019) Vol. 7, pp. 115540-115551
Open Access | Times Cited: 260
Early diagnosis of Parkinson’s disease using machine learning algorithms
Zehra Karapιnar Şentürk
Medical Hypotheses (2020) Vol. 138, pp. 109603-109603
Closed Access | Times Cited: 255
Detecting Parkinson’s disease with sustained phonation and speech signals using machine learning techniques
Jefferson S. Almeida, Pedro P. Rebouças Filho, Tiago Carneiro, et al.
Pattern Recognition Letters (2019) Vol. 125, pp. 55-62
Open Access | Times Cited: 213
Automated Detection of Parkinson’s Disease Based on Multiple Types of Sustained Phonations Using Linear Discriminant Analysis and Genetically Optimized Neural Network
Liaqat Ali, Ce Zhu, Zhonghao Zhang, et al.
IEEE Journal of Translational Engineering in Health and Medicine (2019) Vol. 7, pp. 1-10
Open Access | Times Cited: 177
Artificial intelligence in disease diagnostics: A critical review and classification on the current state of research guiding future direction
Milad Mirbabaie, Stefan Stieglitz, Nicholas Frick
Health and Technology (2021) Vol. 11, Iss. 4, pp. 693-731
Open Access | Times Cited: 161
A Comprehensive Review on AI-Enabled Models for Parkinson’s Disease Diagnosis
Shriniket Dixit, Khitij Bohre, Yashbir Singh, et al.
Electronics (2023) Vol. 12, Iss. 4, pp. 783-783
Open Access | Times Cited: 48
Automatic and Early Detection of Parkinson’s Disease by Analyzing Acoustic Signals Using Classification Algorithms Based on Recursive Feature Elimination Method
Khaled M. Alalayah, Ebrahim Mohammed Senan, Hany F. Atlam, et al.
Diagnostics (2023) Vol. 13, Iss. 11, pp. 1924-1924
Open Access | Times Cited: 41
Early diagnosis of Parkinson’s disease from multiple voice recordings by simultaneous sample and feature selection
Liaqat Ali, Ce Zhu, Mingyi Zhou, et al.
Expert Systems with Applications (2019) Vol. 137, pp. 22-28
Closed Access | Times Cited: 136
Reliable Parkinson’s Disease Detection by Analyzing Handwritten Drawings: Construction of an Unbiased Cascaded Learning System Based on Feature Selection and Adaptive Boosting Model
Liaqat Ali, Ce Zhu, Noorbakhsh Amiri Golilarz, et al.
IEEE Access (2019) Vol. 7, pp. 116480-116489
Open Access | Times Cited: 102
Artificial Intelligence in Clinical Decision Support: a Focused Literature Survey
Stefania Montani, Manuel Striani
Yearbook of Medical Informatics (2019) Vol. 28, Iss. 01, pp. 120-127
Open Access | Times Cited: 95
An efficient dimensionality reduction method using filter-based feature selection and variational autoencoders on Parkinson's disease classification
Hakan Gündüz
Biomedical Signal Processing and Control (2021) Vol. 66, pp. 102452-102452
Closed Access | Times Cited: 89
Optimized ANFIS Model Using Hybrid Metaheuristic Algorithms for Parkinson’s Disease Prediction in IoT Environment
Ibrahim M. El‐Hasnony, Sherif Barakat, Reham R. Mostafa
IEEE Access (2020) Vol. 8, pp. 119252-119270
Open Access | Times Cited: 83
Parkinson’s detection based on combined CNN and LSTM using enhanced speech signals with Variational mode decomposition
Mehmet Bilal Er, Esme Işık, İbrahim Işık
Biomedical Signal Processing and Control (2021) Vol. 70, pp. 103006-103006
Open Access | Times Cited: 75
Sequence-based dynamic handwriting analysis for Parkinson’s disease detection with one-dimensional convolutions and BiGRUs
Moises Díaz, Momina Moetesum, Imran Siddiqi, et al.
Expert Systems with Applications (2020) Vol. 168, pp. 114405-114405
Open Access | Times Cited: 70
Predicting Parkinson’s Disease Progression: Evaluation of Ensemble Methods in Machine Learning
Mehrbakhsh Nilashi, Rabab Ali Abumalloh, Behrouz Minaei-Bidgoli, et al.
Journal of Healthcare Engineering (2022) Vol. 2022, pp. 1-17
Open Access | Times Cited: 61
End-to-end deep learning approach for Parkinson’s disease detection from speech signals
Changqin Quan, Kang Ren, Zhiwei Luo, et al.
Journal of Applied Biomedicine (2022) Vol. 42, Iss. 2, pp. 556-574
Open Access | Times Cited: 59
Binary Grey Wolf Optimizer with Mutation and Adaptive K-nearest Neighbour for Feature Selection in Parkinson’s Disease Diagnosis
R. R. Rajalaxmi, Seyedali Mirjalili, Gothai Ekambaram, et al.
Knowledge-Based Systems (2022) Vol. 246, pp. 108701-108701
Closed Access | Times Cited: 57
Bias Investigation in Artificial Intelligence Systems for Early Detection of Parkinson’s Disease: A Narrative Review
Sudip Paul, Mahesh Maindarkar, Sanjay Saxena, et al.
Diagnostics (2022) Vol. 12, Iss. 1, pp. 166-166
Open Access | Times Cited: 51
Automated methods for diagnosis of Parkinson’s disease and predicting severity level
Zainab Ayaz, Saeeda Naz, Naila Habib Khan, et al.
Neural Computing and Applications (2022)
Closed Access | Times Cited: 45
A novel sample and feature dependent ensemble approach for Parkinson’s disease detection
Liaqat Ali, Chinmay Chakraborty, Zhiquan He, et al.
Neural Computing and Applications (2022) Vol. 35, Iss. 22, pp. 15997-16010
Open Access | Times Cited: 42
Machine learning- and statistical-based voice analysis of Parkinson’s disease patients: A survey
Federica Amato, Giovanni Saggio, Valerio Cesarini, et al.
Expert Systems with Applications (2023) Vol. 219, pp. 119651-119651
Closed Access | Times Cited: 29
Investigation of Scalograms with a Deep Feature Fusion Approach for Detection of Parkinson’s Disease
İsmail Cantürk, Osman Günay
Cognitive Computation (2024) Vol. 16, Iss. 3, pp. 1198-1209
Open Access | Times Cited: 9
Developing a large scale population screening tool for the assessment of Parkinson's disease using telephone-quality voice
Siddharth Arora, Ladan Baghai-Ravary, Athanasios Tsanas
The Journal of the Acoustical Society of America (2019) Vol. 145, Iss. 5, pp. 2871-2884
Open Access | Times Cited: 72
Remote tracking of Parkinson's Disease progression using ensembles of Deep Belief Network and Self-Organizing Map
Mehrbakhsh Nilashi, Hossein Ahmadi, Abbas Sheikhtaheri, et al.
Expert Systems with Applications (2020) Vol. 159, pp. 113562-113562
Closed Access | Times Cited: 62
Autism Spectrum Disorder Detection with Machine Learning Methods
Uğur Erkan, Dang N. H. Thanh
Current Psychiatry Research and Reviews (2019) Vol. 15, Iss. 4, pp. 297-308
Closed Access | Times Cited: 56
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