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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:

Modelling prognostic trajectories of cognitive decline due to Alzheimer's disease
Joseph Giorgio, Susan Landau, William J. Jagust, et al.
NeuroImage Clinical (2020) Vol. 26, pp. 102199-102199
Open Access | Times Cited: 62

Showing 1-25 of 62 citing articles:

Aducanumab: Appropriate Use Recommendations
Joanne Cummings, Paul Aisen, Liana G. Apostolova, et al.
The Journal of Prevention of Alzheimer s Disease (2021), pp. 1-13
Open Access | Times Cited: 228
DEMNET: A Deep Learning Model for Early Diagnosis of Alzheimer Diseases and Dementia From MR Images
Suriya Murugan, Chandran Venkatesan, M. G. Sumithra, et al.
IEEE Access (2021) Vol. 9, pp. 90319-90329
Open Access | Times Cited: 220
Machine learning methods for predicting progression from mild cognitive impairment to Alzheimer’s disease dementia: a systematic review
Sergio Grueso, Raquel Viejo-Sobera
Alzheimer s Research & Therapy (2021) Vol. 13, Iss. 1
Open Access | Times Cited: 185
Artificial intelligence for biomarker discovery in Alzheimer's disease and dementia
Laura Winchester, Eric L. Harshfield, Shi Liu, et al.
Alzheimer s & Dementia (2023) Vol. 19, Iss. 12, pp. 5860-5871
Open Access | Times Cited: 45
Artificial intelligence for diagnostic and prognostic neuroimaging in dementia: A systematic review
Robin Borchert, Tiago Azevedo, AmanPreet Badhwar, et al.
Alzheimer s & Dementia (2023) Vol. 19, Iss. 12, pp. 5885-5904
Open Access | Times Cited: 43
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: 89
Modifiable risk factors for dementia and dementia risk profiling. A user manual for Brain Health Services—part 2 of 6
Janice M. Ranson, Timothy Rittman, Shabina Hayat, et al.
Alzheimer s Research & Therapy (2021) Vol. 13, Iss. 1
Open Access | Times Cited: 78
A robust framework to investigate the reliability and stability of explainable artificial intelligence markers of Mild Cognitive Impairment and Alzheimer’s Disease
Angela Lombardi, Domenico Diacono, Nicola Amoroso, et al.
Brain Informatics (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 41
Robust and interpretable AI-guided marker for early dementia prediction in real-world clinical settings
Liz Yuanxi Lee, Delshad Vaghari, Michael C. Burkhart, et al.
EClinicalMedicine (2024) Vol. 74, pp. 102725-102725
Open Access | Times Cited: 8
Prediction Models for Early Detection of Alzheimer: Recent Trends and Future Prospects
Ishleen Kaur, Rajinder K. Sachdeva
Archives of Computational Methods in Engineering (2025)
Closed Access | Times Cited: 1
The Road to Personalized Medicine in Alzheimer’s Disease: The Use of Artificial Intelligence
Anuschka Silva‐Spínola, Inês Baldeiras, Joel P. Arrais, et al.
Biomedicines (2022) Vol. 10, Iss. 2, pp. 315-315
Open Access | Times Cited: 36
A robust and interpretable machine learning approach using multimodal biological data to predict future pathological tau accumulation
Joseph Giorgio, William J. Jagust, Suzanne L. Baker, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 28
Harnessing the potential of machine learning and artificial intelligence for dementia research
Janice M. Ranson, Magda Bucholc, Donald M. Lyall, et al.
Brain Informatics (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 17
Estimating explainable Alzheimer’s disease likelihood map via clinically-guided prototype learning
Ahmad Wisnu Mulyadi, Wonsik Jung, Kwanseok Oh, et al.
NeuroImage (2023) Vol. 273, pp. 120073-120073
Open Access | Times Cited: 17
Explaining graph convolutional network predictions for clinicians—An explainable AI approach to Alzheimer's disease classification
Sule Tekkesinoglu, Sara Pudas
Frontiers in Artificial Intelligence (2024) Vol. 6
Open Access | Times Cited: 4
A Comprehensive Approach to Anticipating the Progression of Mild Cognitive Impairment
Farah Shahid, Rizwan Khan, Atif Mehmood, et al.
Brain Research (2025), pp. 149549-149549
Closed Access
Ensemble deep learning for Alzheimer’s disease diagnosis using MRI: Integrating features from VGG16, MobileNet, and InceptionResNetV2 models
Meshrif Alruily, A. A. Abd El-Aziz, Ayman Mohamed Mostafa, et al.
PLoS ONE (2025) Vol. 20, Iss. 4, pp. e0318620-e0318620
Open Access
Comparative analysis of machine learning models for Alzheimer’s and dementia differentiation
Glenson Toney, Aldrin Claytus Vaz, J. M. Rathod, et al.
AIP conference proceedings (2025) Vol. 3283, pp. 020034-020034
Closed Access
Targeting the Type 5 Metabotropic Glutamate Receptor: A Potential Therapeutic Strategy for Neurodegenerative Diseases?
Rebecca F. Budgett, Geor Bakker, Eugenia Sergeev, et al.
Frontiers in Pharmacology (2022) Vol. 13
Open Access | Times Cited: 18
Predicting progression and cognitive decline in amyloid-positive patients with Alzheimer’s disease
Hákon Valur Dansson, Lena Stempfle, Hildur Egilsdóttir, et al.
Alzheimer s Research & Therapy (2021) Vol. 13, Iss. 1
Open Access | Times Cited: 21
Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer's Disease
Dan Pan, An Zeng, Baoyao Yang, et al.
Advanced Science (2022) Vol. 10, Iss. 6
Open Access | Times Cited: 16
VGG-C Transform Model with Batch Normalization to Predict Alzheimer’s Disease through MRI Dataset
Batzaya Tuvshinjargal, HeeJoung Hwang
Electronics (2022) Vol. 11, Iss. 16, pp. 2601-2601
Open Access | Times Cited: 15
Artificial Intelligence Techniques for the effective diagnosis of Alzheimer’s Disease: A Review
K. Aditya Shastry, H. A. Sanjay
Multimedia Tools and Applications (2023) Vol. 83, Iss. 13, pp. 40057-40092
Closed Access | Times Cited: 8
Using a ResNet-18 Network to Detect Features of Alzheimer’s Disease on Functional Magnetic Resonance Imaging: A Failed Replication. Comment on Odusami et al. Analysis of Features of Alzheimer’s Disease: Detection of Early Stage from Functional Brain Changes in Magnetic Resonance Images Using a Finetuned ResNet18 Network. Diagnostics 2021, 11, 1071
Peter J. Nicholas, Alex To, Onur Tanglay, et al.
Diagnostics (2022) Vol. 12, Iss. 5, pp. 1094-1094
Open Access | Times Cited: 12
Alzheimer's disease stage recognition from MRI and PET imaging data using Pareto-optimal quantum dynamic optimization
Modupe Odusami, Robertas Damaševičius, Egle Milieškaitė-Belousovienė, et al.
Heliyon (2024) Vol. 10, Iss. 15, pp. e34402-e34402
Open Access | Times Cited: 2
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