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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:

Deep Learning and Neurology: A Systematic Review
Aly Valliani, Daniel Ranti, Eric K. Oermann
Neurology and Therapy (2019) Vol. 8, Iss. 2, pp. 351-365
Open Access | Times Cited: 145

Showing 1-25 of 145 citing articles:

Medical image analysis based on deep learning approach
Murali Krishna Puttagunta, S. Ravi
Multimedia Tools and Applications (2021)
Open Access | Times Cited: 209
Medical deep learning—A systematic meta-review
Jan Egger, Christina Gsaxner, Antonio Pepe, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 221, pp. 106874-106874
Open Access | Times Cited: 172
Gait Analysis in Parkinson’s Disease: An Overview of the Most Accurate Markers for Diagnosis and Symptoms Monitoring
Lazzaro di Biase, Alessandro Di Santo, Maria Letizia Caminiti, et al.
Sensors (2020) Vol. 20, Iss. 12, pp. 3529-3529
Open Access | Times Cited: 163
Neural Decoding of EEG Signals with Machine Learning: A Systematic Review
Maham Saeidi, Waldemar Karwowski, Farzad V. Farahani, et al.
Brain Sciences (2021) Vol. 11, Iss. 11, pp. 1525-1525
Open Access | Times Cited: 131
Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach : A review of two decades of research
Shreyas Gawde, Shruti Patil, Satish Kumar, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106139-106139
Open Access | Times Cited: 130
The topology of fMRI-based networks defines the performance of a graph neural network for the classification of patients with major depressive disorder
Elena Pitsik, V. A. Maximenko, Semen Kurkin, et al.
Chaos Solitons & Fractals (2023) Vol. 167, pp. 113041-113041
Closed Access | Times Cited: 44
Alzheimer’s Disease Detection Using Deep Learning on Neuroimaging: A Systematic Review
Mohammed Alsubaie, Suhuai Luo, Kamran Shaukat
Machine Learning and Knowledge Extraction (2024) Vol. 6, Iss. 1, pp. 464-505
Open Access | Times Cited: 25
Artificial intelligence for brain diseases: A systematic review
Alice Segato, Aldo Marzullo, Francesco Calimeri, et al.
APL Bioengineering (2020) Vol. 4, Iss. 4
Open Access | Times Cited: 122
Diagnosing of disease using machine learning
Pushpa Singh, Narendra Singh, Krishna Kant Singh, et al.
Elsevier eBooks (2021), pp. 89-111
Closed Access | Times Cited: 90
A comprehensive survey of deep learning in the field of medical imaging and medical natural language processing: Challenges and research directions
Babita Pandey, Devendra Kumar Pandey, Brijendra Pratap Mishra, et al.
Journal of King Saud University - Computer and Information Sciences (2021) Vol. 34, Iss. 8, pp. 5083-5099
Closed Access | Times Cited: 88
Artificial Intelligence for Alzheimer’s Disease: Promise or Challenge?
Carlo Fabrizio, Andrea Termine, Carlo Caltagirone, et al.
Diagnostics (2021) Vol. 11, Iss. 8, pp. 1473-1473
Open Access | Times Cited: 86
Early prediction of neoadjuvant chemotherapy response for advanced breast cancer using PET/MRI image deep learning
Joon Ho Choi, Hyun‐Ah Kim, Wook Kim, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 72
Deep learning for neurodegenerative disorder (2016 to 2022): A systematic review
Jyotismita Chaki, Marcin Woźniak
Biomedical Signal Processing and Control (2022) Vol. 80, pp. 104223-104223
Closed Access | Times Cited: 51
Recent advances in deep learning models: a systematic literature review
Ruchika Malhotra, Priya Singh
Multimedia Tools and Applications (2023) Vol. 82, Iss. 29, pp. 44977-45060
Closed Access | Times Cited: 25
Progress and trends in neurological disorders research based on deep learning
Muhammad Shahid Iqbal, Md Belal Bin Heyat, Saba Parveen, et al.
Computerized Medical Imaging and Graphics (2024) Vol. 116, pp. 102400-102400
Closed Access | Times Cited: 9
An Exploratory Review of Machine Learning and Deep Learning Applications in Healthcare Management
Narasimha Rao Vajjhala, Philip Eappen
Springer proceedings in mathematics & statistics (2025), pp. 315-324
Closed Access | Times Cited: 1
MULTI-DEEP: A novel CAD system for coronavirus (COVID-19) diagnosis from CT images using multiple convolution neural networks
Omneya Attallah, Dina A. Ragab, Maha Sharkas
PeerJ (2020) Vol. 8, pp. e10086-e10086
Open Access | Times Cited: 61
Transparency and Trust in Human-AI-Interaction: The Role of Model-Agnostic Explanations in Computer Vision-Based Decision Support
Christian Meske, Enrico Bunde
Lecture notes in computer science (2020), pp. 54-69
Open Access | Times Cited: 58
Artificial Intelligence in Clinical Neuroscience: Methodological and Ethical Challenges
Marcello Ienca, Karolina Ignatiadis
AJOB Neuroscience (2020) Vol. 11, Iss. 2, pp. 77-87
Closed Access | Times Cited: 56
Artificial Intelligence and Computational Approaches for Epilepsy
Sora An, Chaewon Kang, Hyang Woon Lee
Journal of Epilepsy Research (2020) Vol. 10, Iss. 1, pp. 8-17
Open Access | Times Cited: 51
Artificial Intelligence: Review of Current and Future Applications in Medicine
L. Brannon Thomas, Stephen Mastorides, Narayan Viswanadhan, et al.
Federal practitioner (2021), Iss. 38 (11)
Open Access | Times Cited: 45
Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research
Fabian Eitel, Marc‐Andre Schulz, Moritz Seiler, et al.
Experimental Neurology (2021) Vol. 339, pp. 113608-113608
Open Access | Times Cited: 43
Neuroimaging in the Era of Artificial Intelligence: Current Applications
Robert Monsour
Federal practitioner (2022), Iss. 39 (Suppl 1)
Open Access | Times Cited: 36
A review on Alzheimer’s disease classification from normal controls and mild cognitive impairment using structural MR images
Neha Garg, Mahipal Singh Choudhry, Rajesh M. Bodade
Journal of Neuroscience Methods (2022) Vol. 384, pp. 109745-109745
Closed Access | Times Cited: 34
Deep Learning in mHealth for Cardiovascular Disease, Diabetes, and Cancer: Systematic Review
Andreas Triantafyllidis, Haridimos Kondylakis, Dimitrios G. Katehakis, et al.
JMIR mhealth and uhealth (2022) Vol. 10, Iss. 4, pp. e32344-e32344
Open Access | Times Cited: 33
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