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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:

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: 45

Showing 1-25 of 45 citing articles:

Modified U-NET Architecture for Segmentation of Skin Lesion
Vatsala Anand, Sheifali Gupta, Deepika Koundal, et al.
Sensors (2022) Vol. 22, Iss. 3, pp. 867-867
Open Access | Times Cited: 120
Artificial Intelligence-Based Voice Assessment of Patients with Parkinson’s Disease Off and On Treatment: Machine vs. Deep-Learning Comparison
Giovanni Costantini, Valerio Cesarini, Pietro Leo, et al.
Sensors (2023) Vol. 23, Iss. 4, pp. 2293-2293
Open Access | Times Cited: 45
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
Cardiovascular/Stroke Risk Stratification in Parkinson’s Disease Patients Using Atherosclerosis Pathway and Artificial Intelligence Paradigm: A Systematic Review
Jasjit S. Suri, Sudip Paul, Mahesh Maindarkar, et al.
Metabolites (2022) Vol. 12, Iss. 4, pp. 312-312
Open Access | Times Cited: 38
Intelligent speech technologies for transcription, disease diagnosis, and medical equipment interactive control in smart hospitals: A review
Jun Zhang, Jingyue Wu, Yiyi Qiu, et al.
Computers in Biology and Medicine (2023) Vol. 153, pp. 106517-106517
Open Access | Times Cited: 33
Breast cancer diagnosis based on hybrid rule-based feature selection with deep learning algorithm
Joseph Bamidele Awotunde, Ranjit Panigrahi, Bidita Khandelwal, et al.
Research on Biomedical Engineering (2023) Vol. 39, Iss. 1, pp. 115-127
Closed Access | Times Cited: 23
An Efficient Machine Learning Approach for Diagnosing Parkinson’s Disease by Utilizing Voice Features
Arti Rana, Ankur Dumka, Rajesh Singh, et al.
Electronics (2022) Vol. 11, Iss. 22, pp. 3782-3782
Open Access | Times Cited: 28
Automatic detection of Parkinson’s disease using machine learning and deep learning: A recent literature review
Rani Oomman Panicker, D. Yashasvi, Jodi James, et al.
Ethics Medicine and Public Health (2025) Vol. 33, pp. 101079-101079
Closed Access
Artificial intelligence-enabled detection and assessment of Parkinson’s disease using multimodal data: A survey
Aite Zhao, Yongcan Liu, Xinglin Yu, et al.
Information Fusion (2025), pp. 103175-103175
Closed Access
Assessment of Acoustic Features and Machine Learning for Parkinson’s Detection
Moumita Pramanik, Ratika Pradhan, Parvati Nandy, et al.
Journal of Healthcare Engineering (2021) Vol. 2021, pp. 1-13
Open Access | Times Cited: 27
PADG‐Pred: Exploring Ensemble Approaches for Identifying Parkinson's Disease Associated Biomarkers Using Genomic Sequences Analysis
Ayesha Karim, Tamim Alkhalifah, Fahad Alturise, et al.
IET Systems Biology (2025) Vol. 19, Iss. 1
Open Access
Hybrid Feature Selection Framework for the Parkinson Imbalanced Dataset Prediction Problem
Hayder Mohammed Qasim, Oğuz Ata, Mohammad Azam Ansari, et al.
Medicina (2021) Vol. 57, Iss. 11, pp. 1217-1217
Open Access | Times Cited: 25
A machine learning approach in spatial predicting of landslides and flash flood susceptible zones for a road network
Hang Ha, Quynh Duy Bui, Thanh Dong Khuc, et al.
Modeling Earth Systems and Environment (2022) Vol. 8, Iss. 4, pp. 4341-4357
Closed Access | Times Cited: 18
An adaptive intelligent diagnostic system to predict early stage of parkinson's disease using two-stage dimension reduction with genetically optimized lightgbm algorithm
Joy Dhar
Neural Computing and Applications (2021) Vol. 34, Iss. 6, pp. 4567-4593
Closed Access | Times Cited: 20
A Computerized Analysis with Machine Learning Techniques for the Diagnosis of Parkinson’s Disease: Past Studies and Future Perspectives
Arti Rana, Ankur Dumka, Rajesh Singh, et al.
Diagnostics (2022) Vol. 12, Iss. 11, pp. 2708-2708
Open Access | Times Cited: 15
A new Diagnosis using a Parkinson's Disease XGBoost and CNN-based classification model Using ML Techniques
Anil Kumar N, Bhavini Rajendrakumar Bhatt, P. Anitha, et al.
(2022)
Closed Access | Times Cited: 14
Analysis of Parkinson’s Disease Using an Imbalanced-Speech Dataset by Employing Decision Tree Ensemble Methods
Omar Barukab, Amir Ahmad, Tabrej Khan, et al.
Diagnostics (2022) Vol. 12, Iss. 12, pp. 3000-3000
Open Access | Times Cited: 14
Integration of Machine Learning and IoT in Healthcare Domain
Ananya Chattopadhyay, Sushruta Mishra, Alfonso González‐Briones
Intelligent systems reference library (2021), pp. 223-244
Closed Access | Times Cited: 17
Remote Patient Monitoring Using IoT, Cloud Computing and AI
M. V. V. Prasad Kantipudi, C. John Moses, Rajanikanth Aluvalu, et al.
Intelligent systems reference library (2021), pp. 51-74
Closed Access | Times Cited: 16
An Efficient Rotation Forest-Based Ensemble Approach for Predicting Severity of Parkinson’s Disease
Saeid Sheikhi, Mohammad Taghi Kheirabadi
Journal of Healthcare Engineering (2022) Vol. 2022, pp. 1-9
Open Access | Times Cited: 12
An efficient lightweight speck technique for edge-IoT-based smart healthcare systems
Muyideen AbdulRaheem, Idowu Dauda Oladipo, Alfonso González‐Briones, et al.
Elsevier eBooks (2022), pp. 139-162
Closed Access | Times Cited: 11
Universal intraensemble method using nonlinear AI techniques for regression modeling of small medical data sets
Ivan Izonin, Roman Tkachenko
Elsevier eBooks (2022), pp. 123-150
Closed Access | Times Cited: 10
Enhancing Parkinson’s disease identification using ensemble classifier and data augmentation techniques in machine learning
Mohammed Muzaffar Hussain, D. Weslin, Sunita Kumari, et al.
Clinical eHealth (2023) Vol. 6, pp. 150-158
Open Access | Times Cited: 5
Exploring The Potential of Machine Learning for Early Diagnosis of Parkinson's Disease: A Comparative Study
Devi Padma K, P Harshitha, R Nafiza, et al.
(2023) Vol. 3, pp. 1-6
Closed Access | Times Cited: 4
HEFS-MLDR: A novel hybrid ensemble feature selection framework for improved deep neural network architecture in the diagnosis of Parkinson’s disease
Asmae Ouhmida, Shawki Saleh, Abderazzak Ammar, et al.
Multimedia Tools and Applications (2024)
Closed Access | Times Cited: 1
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