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:

Disentangling Alzheimer’s disease neurodegeneration from typical brain ageing using machine learning
Gyujoon Hwang, Ahmed Abdulkadir, Guray Erus, et al.
Brain Communications (2022) Vol. 4, Iss. 3
Open Access | Times Cited: 20

Showing 20 citing articles:

A deep learning model for brain age prediction using minimally preprocessed T1w images as input
Caroline Machado Dartora, Anna Marseglia, Gustav Mårtensson, et al.
Frontiers in Aging Neuroscience (2024) Vol. 15
Open Access | Times Cited: 17
Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study
Peter R Millar, Brian A. Gordon, Patrick H. Luckett, et al.
eLife (2023) Vol. 12
Open Access | Times Cited: 33
Brain age prediction using the graph neural network based on resting-state functional MRI in Alzheimer's disease
Jingjing Gao, Jiaxin Liu, Yuhang Xu, et al.
Frontiers in Neuroscience (2023) Vol. 17
Open Access | Times Cited: 18
Genetic and Clinical Correlates of AI-Based Brain Aging Patterns in Cognitively Unimpaired Individuals
Ioanna Skampardoni, Ilya M. Nasrallah, Ahmed Abdulkadir, et al.
JAMA Psychiatry (2024) Vol. 81, Iss. 5, pp. 456-456
Closed Access | Times Cited: 6
Assessment of Neuroanatomical Endophenotypes of Autism Spectrum Disorder and Association With Characteristics of Individuals With Schizophrenia and the General Population
Gyujoon Hwang, Junhao Wen, Susan Sotardi, et al.
JAMA Psychiatry (2023) Vol. 80, Iss. 5, pp. 498-498
Open Access | Times Cited: 15
Tau‐neurodegeneration mismatch reveals vulnerability and resilience to comorbidities in Alzheimer's continuum
Xueying Lyu, Michael Tran Duong, Long Xie, et al.
Alzheimer s & Dementia (2023) Vol. 20, Iss. 3, pp. 1586-1600
Open Access | Times Cited: 11
Transforming Neurodegenerative Disorder Care with Machine Learning: Strategies and Applications
Aya Galal, Ahmed A. Moustafa, Mohamed Salama
(2025)
Closed Access
Transforming neurodegenerative disorder care with machine learning: Strategies and applications
Aya Galal, Ahmed A. Moustafa, Mohamed Salama
Neuroscience (2025)
Closed Access
Differential diagnosis of frontotemporal dementia subtypes with explainable deep learning on structural MRI
Da Ma, Jane Stocks, Howard J. Rosen, et al.
Frontiers in Neuroscience (2024) Vol. 18
Open Access | Times Cited: 3
NODDI in gray matter is a sensitive marker of aging and early AD changes
Xi Yu, Scott A. Przybelski, Robert I. Reid, et al.
Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring (2024) Vol. 16, Iss. 3
Open Access | Times Cited: 3
Disentangling Neurodegeneration From Aging in Multiple Sclerosis Using Deep Learning
Giuseppe Pontillo, Ferrán Prados, Jordan Colman, et al.
Neurology (2024) Vol. 103, Iss. 10
Closed Access | Times Cited: 3
Disentangling Accelerated Cognitive Decline from the Normal Aging Process and Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach
Yulin Dai, Yu‐Chun Hsu, Brisa S. Fernandes, et al.
Journal of Alzheimer s Disease (2024) Vol. 97, Iss. 4, pp. 1807-1827
Open Access | Times Cited: 1
Relationship between MRI brain-age heterogeneity, cognition, genetics and Alzheimer’s disease neuropathology
Mathilde Antoniades, Dhivya Srinivasan, Junhao Wen, et al.
EBioMedicine (2024) Vol. 109, pp. 105399-105399
Closed Access | Times Cited: 1
Predicting Brain Age Using Transferable Covariance Neural Networks
Saurabh Sihag, Gonzalo Mateos, Corey T. McMillan, et al.
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2023), pp. 1-5
Open Access | Times Cited: 2
Disentangling neurodegeneration from ageing in multiple sclerosis: the brain-predicted disease duration gap
Giuseppe Pontillo, Ferrán Prados, Jordan Colman, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Power of Ensemble Techniques for Brain Age Prediction Using Machine Learning Models
V. Ravi, Himanshu Singh Baghel, Nainika Chinamsetty, et al.
Research Square (Research Square) (2024)
Open Access
Tau-Neurodegenerationmismatchreveals vulnerability and resilience to comorbidities in Alzheimer’s continuum
Xueying Lyu, Michael Tran Duong, Long Xie, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 1
Disentangling accelerated cognitive decline from the normal aging process and unraveling its genetic components: A neuroimaging-based deep learning approach
Yulin Dai, Yu‐Chun Hsu, Brisa S. Fernandes, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 1
Three Imaging Endophenotypes Characterize Neuroanatomical Heterogeneity of Autism Spectrum Disorder
Gyujoon Hwang, Junhao Wen, Susan Sotardi, et al.
Research Square (Research Square) (2022)
Open Access | Times Cited: 1
Three Imaging Endophenotypes Characterize Neuroanatomical Heterogeneity of Autism Spectrum Disorder
Gyujoon Hwang, Junhao Wen, Susan Sotardi, et al.
medRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 1
Page 1

Scroll to top