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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 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: 178

Showing 1-25 of 178 citing articles:

A deep learning based convolutional neural network model with VGG16 feature extractor for the detection of Alzheimer Disease using MRI scans
Shagun Sharma, Kalpna Guleria, Sunita Tiwari, et al.
Measurement Sensors (2022) Vol. 24, pp. 100506-100506
Open Access | Times Cited: 109
Deep learning-based classification of healthy aging controls, mild cognitive impairment and Alzheimer’s disease using fusion of MRI-PET imaging
V.P. Subramanyam Rallabandi, Krishnamoorthy Seetharaman
Biomedical Signal Processing and Control (2022) Vol. 80, pp. 104312-104312
Closed Access | Times Cited: 44
Diabetes and cognitive function: An evidence-based current perspective
Meghna Julian Sebastian, Shahanas K A Khan, Joseph M. Pappachan, et al.
World Journal of Diabetes (2023) Vol. 14, Iss. 2, pp. 92-109
Open Access | Times Cited: 35
The Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022
Dallas P. Veitch, Michael W. Weiner, Melanie J. Miller, et al.
Alzheimer s & Dementia (2023) Vol. 20, Iss. 1, pp. 652-694
Open Access | Times Cited: 35
A Logistic Regression and Decision Tree Based Hybrid Approach to Predict Alzheimer's Disease
Tushar Tushar, Richa Kamleshkumar Patel, Eshant Aggarwal, et al.
2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) (2023), pp. 722-726
Closed Access | Times Cited: 23
A systematic literature review on the significance of deep learning and machine learning in predicting Alzheimer's disease
Arshdeep Kaur, Meenakshi Mittal, Jasvinder Singh Bhatti, et al.
Artificial Intelligence in Medicine (2024) Vol. 154, pp. 102928-102928
Closed Access | Times Cited: 13
Deep learning methods for early detection of Alzheimer’s disease using structural MR images: a survey
Sonia Ben Hassen, Mohamed Néji, Zain Hussain, et al.
Neurocomputing (2024) Vol. 576, pp. 127325-127325
Closed Access | Times Cited: 10
Distinct plasma phosphorylated-tau proteins profiling for the differential diagnosis of mild cognitive impairment and Alzheimer's disease by plasmonic asymmetric nanobridge-based biosensor
Soohyun Kim, Xingyi Ma, Myeong Jin Jeon, et al.
Biosensors and Bioelectronics (2024) Vol. 250, pp. 116085-116085
Closed Access | Times Cited: 8
ALZENET: Deep Learning-Based Early Prediction of Alzheimer's Disease through Magnetic Resonance Imaging Analysis
Md. Asaduzzaman, Md. Khorshed Alom, Md. Masudul Karim
Telematics and Informatics Reports (2025), pp. 100189-100189
Open Access | Times Cited: 1
An Interpretable PyCaret Approach for Alzheimer's Disease Prediction
A. P., R. Gunasundari
International Journal of Computational and Experimental Science and Engineering (2024) Vol. 10, Iss. 4
Open Access | Times Cited: 7
Machine learning, artificial intelligence and the prediction of dementia
Alexander Merkin, Rita Krishnamurthi, Oleg N. Medvedev
Current Opinion in Psychiatry (2021) Vol. 35, Iss. 2, pp. 123-129
Closed Access | Times Cited: 40
Epigenetic Peripheral Biomarkers for Early Diagnosis of Alzheimer’s Disease
Chiara Villa, Andrea Stoccoro
Genes (2022) Vol. 13, Iss. 8, pp. 1308-1308
Open Access | Times Cited: 25
Abnormal regional homogeneity in right caudate as a potential neuroimaging biomarker for mild cognitive impairment: A resting-state fMRI study and support vector machine analysis
Yujun Gao, Xinfu Zhao, Jichao Huang, et al.
Frontiers in Aging Neuroscience (2022) Vol. 14
Open Access | Times Cited: 23
Predicting cognitive decline in Parkinson’s disease using FDG-PET–based supervised learning
Samuel Booth, Kye Won Park, Chong Sik Lee, et al.
Journal of Clinical Investigation (2022) Vol. 132, Iss. 20
Open Access | Times Cited: 22
Artificial intelligence for dementia research methods optimization
Magda Bucholc, Charlotte James, Ahmad Al Khleifat, et al.
Alzheimer s & Dementia (2023) Vol. 19, Iss. 12, pp. 5934-5951
Open Access | Times Cited: 15
Classification of suicidality by training supervised machine learning models with brain MRI findings: A systematic review
Mohammadamin Parsaei, Fateme Taghavizanjani, Giulia Cattarinussi, et al.
Journal of Affective Disorders (2023) Vol. 340, pp. 766-791
Closed Access | Times Cited: 14
Systematic reviews of machine learning in healthcare: a literature review
Katarzyna Kolasa, Bisrat Yeshewas Admassu, Malwina Hołownia-Voloskova, et al.
Expert Review of Pharmacoeconomics & Outcomes Research (2023) Vol. 24, Iss. 1, pp. 63-115
Open Access | Times Cited: 14
Significant Acceleration of Regional Brain Aging and Atrophy After Mild Traumatic Brain Injury
Alexander F Shida, Roy J Massett, Phoebe Imms, et al.
The Journals of Gerontology Series A (2023) Vol. 78, Iss. 8, pp. 1328-1338
Closed Access | Times Cited: 13
PRedicting the EVolution of SubjectIvE Cognitive Decline to Alzheimer’s Disease With machine learning: the PREVIEW study protocol
Salvatore Mazzeo, Michael Lassi, Sonia Padiglioni, et al.
BMC Neurology (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 13
Integrating machine learning and artificial intelligence in life-course epidemiology: pathways to innovative public health solutions
Shanquan Chen, Jiazhou Yu, Sarah Chamouni, et al.
BMC Medicine (2024) Vol. 22, Iss. 1
Open Access | Times Cited: 4
Development of a predictive model for loss of functional and cognitive abilities in long-term care home residents: a protocol
Christina Y Yin, Robert Talarico, Mary Scott, et al.
BMJ Open (2025) Vol. 15, Iss. 1, pp. e086935-e086935
Open Access
Transfer from long-term care to acute care and risk of new permanent cognitive or physical disability among long-term care residents in Canada: protocol for a retrospective cohort study
Christina Y Yin, Mary Scott, Robert Talarico, et al.
BMJ Open (2025) Vol. 15, Iss. 1, pp. e086932-e086932
Open Access
From pixels to prognosis: radiomics and AI in Alzheimer’s disease management
Dequn Peng, Weiyi Huang, Ren Ping Liu, et al.
Frontiers in Neurology (2025) Vol. 16
Open Access
Alzheimer stages prediction using swinnet for segmentation and transfer learning based CATNet approach with SBO algorithm
Bhuvaneshwari Jolad, Mala Rao, Subhash Y. Kamdi, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2025) Vol. 8, Iss. 2
Closed Access
Multimodal fusion diagnosis of the Alzheimer’s disease via lightweight CNN-LSTM model using magnetic resonance imaging (MRI)
Ejaz Ul Haq, Yong Qin, Yuan Zhou, et al.
Biomedical Signal Processing and Control (2025) Vol. 104, pp. 107545-107545
Closed Access
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