Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Convolutional Neural Networks for Neuroimaging in Parkinson’s Disease: Is Preprocessing Needed?
Francisco J. Martínez-Murcia, J. M. Górriz, Javier Ramı́rez, et al.
International Journal of Neural Systems (2018) Vol. 28, Iss. 10, pp. 1850035-1850035
Open Access | Times Cited: 96

Showing 1-25 of 96 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
Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications
J. M. Górriz, Javier Ramı́rez, Andrés Ortíz, et al.
Neurocomputing (2020) Vol. 410, pp. 237-270
Open Access | Times Cited: 239
Automated Depression Detection Using Deep Representation and Sequence Learning with EEG Signals
Betül Ay, Özal Yıldırım, Muhammed Talo, et al.
Journal of Medical Systems (2019) Vol. 43, Iss. 7
Closed Access | Times Cited: 238
Studying the Manifold Structure of Alzheimer's Disease: A Deep Learning Approach Using Convolutional Autoencoders
Francisco J. Martínez-Murcia, Andrés Ortíz, J. M. Górriz, et al.
IEEE Journal of Biomedical and Health Informatics (2019) Vol. 24, Iss. 1, pp. 17-26
Open Access | Times Cited: 200
An Explainable Machine Learning Model for Early Detection of Parkinson's Disease using LIME on DaTSCAN Imagery
Pavan Rajkumar Magesh, Richard Delwin Myloth, Rijo Jackson Tom
Computers in Biology and Medicine (2020) Vol. 126, pp. 104041-104041
Open Access | Times Cited: 192
Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review
Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari, et al.
Computers in Biology and Medicine (2021) Vol. 136, pp. 104697-104697
Open Access | Times Cited: 144
DepHNN: A novel hybrid neural network for electroencephalogram (EEG)-based screening of depression
Geetanjali Sharma, Abhishek Parashar, Amit M. Joshi
Biomedical Signal Processing and Control (2021) Vol. 66, pp. 102393-102393
Closed Access | Times Cited: 141
Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends
J. M. Górriz, I. Álvarez, Agustín Álvarez-Marquina, et al.
Information Fusion (2023) Vol. 100, pp. 101945-101945
Open Access | Times Cited: 96
A review of machine learning and deep learning algorithms for Parkinson's disease detection using handwriting and voice datasets
Md Ariful Islam, Md. Ziaul Hasan Majumder, Md. Alomgeer Hussein, et al.
Heliyon (2024) Vol. 10, Iss. 3, pp. e25469-e25469
Open Access | Times Cited: 19
A novel end‐to‐end deep learning scheme for classifying multi‐class motor imagery electroencephalography signals
Ahmad Hassanpour, Majid Moradikia, Hojjat Adeli, et al.
Expert Systems (2019) Vol. 36, Iss. 6
Closed Access | Times Cited: 132
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
Parkinson's Disease Detection Using Isosurfaces-Based Features and Convolutional Neural Networks
Andrés Ortíz, Jorge Munilla, Manuel Martínez-Ibañez, et al.
Frontiers in Neuroinformatics (2019) Vol. 13
Open Access | Times Cited: 80
Application of Deep Learning Models for Automated Identification of Parkinson’s Disease: A Review (2011–2021)
Hui Wen Loh, Wanrong Hong, Chui Ping Ooi, et al.
Sensors (2021) Vol. 21, Iss. 21, pp. 7034-7034
Open Access | Times Cited: 80
Detection of Mild Cognitive Impairment Using Convolutional Neural Network: Temporal-Feature Maps of Functional Near-Infrared Spectroscopy
Dalin Yang, Ruisen Huang, So-Hyeon Yoo, et al.
Frontiers in Aging Neuroscience (2020) Vol. 12
Open Access | Times Cited: 79
Uncertainty-driven ensembles of multi-scale deep architectures for image classification
Juan E. Arco, Andrés Ortíz, Javier Ramı́rez, et al.
Information Fusion (2022) Vol. 89, pp. 53-65
Open Access | Times Cited: 42
Diagnostic performance of artificial intelligence-assisted PET imaging for Parkinson’s disease: a systematic review and meta-analysis
Jing Wang, Le Xue, Jiehui Jiang, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 12
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
Deep residual transfer learning for automatic diagnosis and grading of diabetic retinopathy
Francisco J. Martínez-Murcia, Andrés Ortíz, Javier Ramı́rez, et al.
Neurocomputing (2020) Vol. 452, pp. 424-434
Open Access | Times Cited: 69
A convolutional neural network-based system to classify patients using FDG PET/CT examinations
Keisuke Kawauchi, Sho Furuya, Kenji Hirata, et al.
BMC Cancer (2020) Vol. 20, Iss. 1
Open Access | Times Cited: 65
Quantification of water inflow in rock tunnel faces via convolutional neural network approach
Jiayao Chen, Mingliang Zhou, Dongming Zhang, et al.
Automation in Construction (2020) Vol. 123, pp. 103526-103526
Closed Access | Times Cited: 58
Image-based segmentation and quantification of weak interlayers in rock tunnel face via deep learning
Jiayao Chen, Dongming Zhang, Hongwei Huang, et al.
Automation in Construction (2020) Vol. 120, pp. 103371-103371
Closed Access | Times Cited: 51
Upper Limb Movement Classification Via Electromyographic Signals and an Enhanced Probabilistic Network
Alexis Burns, Hojjat Adeli, John A. Buford
Journal of Medical Systems (2020) Vol. 44, Iss. 10
Closed Access | Times Cited: 50
The Role of Neural Network for the Detection of Parkinson’s Disease: A Scoping Review
Mahmood Alzubaidi, Uzair Shah, Haider Dhia Zubaydi, et al.
Healthcare (2021) Vol. 9, Iss. 6, pp. 740-740
Open Access | Times Cited: 49
Efficient detection of Parkinson's disease using deep learning techniques over medical data
Lipsita Sahu, Rohit Sharma, Ipsita Sahu, et al.
Expert Systems (2021) Vol. 39, Iss. 3
Closed Access | Times Cited: 47
Deep Learning-based Transfer Learning Model in Diagnosis of Diseases with Brain Magnetic Resonance Imaging
R.C. Suganthe, Geetha Muthusamy, Latha Rukmani Sevalaiappan, et al.
Acta Polytechnica Hungarica (2022) Vol. 19, Iss. 5, pp. 127-147
Open Access | Times Cited: 35
Page 1 - Next Page

Scroll to top