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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:

Accurate brain age prediction with lightweight deep neural networks
Han Peng, Weikang Gong, Christian F. Beckmann, et al.
Medical Image Analysis (2020) Vol. 68, pp. 101871-101871
Open Access | Times Cited: 374

Showing 1-25 of 374 citing articles:

Heterogeneous aging across multiple organ systems and prediction of chronic disease and mortality
Ye Tian, Vanessa Cropley, Andrea B. Maier, et al.
Nature Medicine (2023) Vol. 29, Iss. 5, pp. 1221-1231
Open Access | Times Cited: 270
Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets
Marc‐Andre Schulz, B.T. Thomas Yeo, Joshua T Vogelstein, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 236
Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning
Anees Abrol, Zening Fu, Mustafa S. Salman, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 163
Machine learning for brain age prediction: Introduction to methods and clinical applications
Lea Baecker, Rafael Garcia‐Dias, Sandra Vieira, et al.
EBioMedicine (2021) Vol. 72, pp. 103600-103600
Open Access | Times Cited: 162
Deep learning-based brain age prediction in normal aging and dementia
Jeyeon Lee, Brian J. Burkett, Hoon‐Ki Min, et al.
Nature Aging (2022) Vol. 2, Iss. 5, pp. 412-424
Open Access | Times Cited: 122
Mind the gap: Performance metric evaluation in brain‐age prediction
Ann‐Marie G. de Lange, Melis Anatürk, Jaroslav Rokicki, et al.
Human Brain Mapping (2022) Vol. 43, Iss. 10, pp. 3113-3129
Open Access | Times Cited: 101
Deep neural networks learn general and clinically relevant representations of the ageing brain
Esten H. Leonardsen, Han Peng, Tobias Kaufmann, et al.
NeuroImage (2022) Vol. 256, pp. 119210-119210
Open Access | Times Cited: 99
Deep learning for brain age estimation: A systematic review
M. Tanveer, M. A. Ganaie, Iman Beheshti, et al.
Information Fusion (2023) Vol. 96, pp. 130-143
Open Access | Times Cited: 80
Anatomically interpretable deep learning of brain age captures domain-specific cognitive impairment
Chenzhong Yin, Phoebe Imms, Mingxi Cheng, et al.
Proceedings of the National Academy of Sciences (2023) Vol. 120, Iss. 2
Open Access | Times Cited: 66
Brain-age prediction: A systematic comparison of machine learning workflows
Shammi More, Georgios Antonopoulos, Felix Hoffstaedter, et al.
NeuroImage (2023) Vol. 270, pp. 119947-119947
Open Access | Times Cited: 64
Investigating the impact of motion in the scanner on brain age predictions
Roqaie Moqadam, Mahsa Dadar, Yashar Zeighami
Imaging Neuroscience (2024) Vol. 2, pp. 1-21
Open Access | Times Cited: 27
The genetic architecture of multimodal human brain age
Junhao Wen, Bingxin Zhao, Zhijian Yang, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 21
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
Hyperfusion: A hypernetwork approach to multimodal integration of tabular and medical imaging data for predictive modeling
Daniel Duenias, Brennan Nichyporuk, Tal Arbel, et al.
Medical Image Analysis (2025) Vol. 102, pp. 103503-103503
Open Access | Times Cited: 3
Classifying Autism Spectrum Disorder Using the Temporal Statistics of Resting-State Functional MRI Data With 3D Convolutional Neural Networks
Rajat M. Thomas, Selene Gallo, Leonardo Cerliani, et al.
Frontiers in Psychiatry (2020) Vol. 11
Open Access | Times Cited: 102
Brain age prediction: A comparison between machine learning models using region‐ and voxel‐based morphometric data
Lea Baecker, Jessica Dafflon, Pedro F. da Costa, et al.
Human Brain Mapping (2021) Vol. 42, Iss. 8, pp. 2332-2346
Open Access | Times Cited: 87
Deep learning applications for the classification of psychiatric disorders using neuroimaging data: Systematic review and meta-analysis
Mirjam Quaak, Laurens van de Mortel, Rajat M. Thomas, et al.
NeuroImage Clinical (2021) Vol. 30, pp. 102584-102584
Open Access | Times Cited: 72
Cardiometabolic risk factors associated with brain age and accelerate brain ageing
Dani Beck, Ann‐Marie G. de Lange, Mads L. Pedersen, et al.
Human Brain Mapping (2021) Vol. 43, Iss. 2, pp. 700-720
Open Access | Times Cited: 72
Explainable Deep Learning for Personalized Age Prediction With Brain Morphology
Angela Lombardi, Domenico Diacono, Nicola Amoroso, et al.
Frontiers in Neuroscience (2021) Vol. 15
Open Access | Times Cited: 63
Multi-channel attention-fusion neural network for brain age estimation: Accuracy, generality, and interpretation with 16,705 healthy MRIs across lifespan
Sheng He, Diana Pereira, Juan David Perez, et al.
Medical Image Analysis (2021) Vol. 72, pp. 102091-102091
Open Access | Times Cited: 57
Graph Transformer Geometric Learning of Brain Networks Using Multimodal MR Images for Brain Age Estimation
Hongjie Cai, Yue Gao, Manhua Liu
IEEE Transactions on Medical Imaging (2022) Vol. 42, Iss. 2, pp. 456-466
Closed Access | Times Cited: 45
Multimodal biological brain age prediction using magnetic resonance imaging and angiography with the identification of predictive regions
Pauline Mouchès, Matthias Wilms, Deepthi Rajashekar, et al.
Human Brain Mapping (2022) Vol. 43, Iss. 8, pp. 2554-2566
Open Access | Times Cited: 39
Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer’s disease and neurodegeneration stratified by sex
Irene Cumplido‐Mayoral, Marina García‐Prat, Grégory Operto, et al.
eLife (2023) Vol. 12
Open Access | Times Cited: 35
Linking brain maturation and puberty during early adolescence using longitudinal brain age prediction in the ABCD cohort
Madelene Holm, Esten H. Leonardsen, Dani Beck, et al.
Developmental Cognitive Neuroscience (2023) Vol. 60, pp. 101220-101220
Open Access | Times Cited: 32
Prediction of brain age using structural magnetic resonance imaging: A comparison of accuracy and test–retest reliability of publicly available software packages
Ruben P. Dörfel, Joan M. Arenas‐Gomez, Patrick M. Fisher, et al.
Human Brain Mapping (2023) Vol. 44, Iss. 17, pp. 6139-6148
Open Access | Times Cited: 29
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