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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:

Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site FMRI data
Weizheng Yan, Vince D. Calhoun, Ming Song, et al.
EBioMedicine (2019) Vol. 47, pp. 543-552
Open Access | Times Cited: 151

Showing 1-25 of 151 citing articles:

A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises
S. Kevin Zhou, Hayit Greenspan, Christos Davatzikos, et al.
Proceedings of the IEEE (2021) Vol. 109, Iss. 5, pp. 820-838
Open Access | Times Cited: 691
Neuroimaging-based Individualized Prediction of Cognition and Behavior for Mental Disorders and Health: Methods and Promises
Jing Sui, Rongtao Jiang, Juan Bustillo, et al.
Biological Psychiatry (2020) Vol. 88, Iss. 11, pp. 818-828
Open Access | Times Cited: 269
A Survey on Deep Learning for Neuroimaging-Based Brain Disorder Analysis
Li Zhang, Mingliang Wang, Mingxia Liu, et al.
Frontiers in Neuroscience (2020) Vol. 14
Open Access | Times Cited: 168
Deep learning for small and big data in psychiatry
Georgia Koppe, Andreas Meyer‐Lindenberg, Daniel Durstewitz
Neuropsychopharmacology (2020) Vol. 46, Iss. 1, pp. 176-190
Open Access | Times Cited: 162
An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future works
Delaram Sadeghi, Afshin Shoeibi, Navid Ghassemi, et al.
Computers in Biology and Medicine (2022) Vol. 146, pp. 105554-105554
Open Access | Times Cited: 128
Cross-ethnicity/race generalization failure of behavioral prediction from resting-state functional connectivity
Jingwei Li, Danilo Bzdok, Jianzhong Chen, et al.
Science Advances (2022) Vol. 8, Iss. 11
Open Access | Times Cited: 111
Modern views of machine learning for precision psychiatry
Zhe Chen, Prathamesh Kulkarni, Isaac R. Galatzer‐Levy, et al.
Patterns (2022) Vol. 3, Iss. 11, pp. 100602-100602
Open Access | Times Cited: 86
Natural and Artificial Intelligence: A brief introduction to the interplay between AI and neuroscience research
Tom Macpherson, Anne K. Churchland, Terry Sejnowski, et al.
Neural Networks (2021) Vol. 144, pp. 603-613
Open Access | Times Cited: 102
A dynamic graph convolutional neural network framework reveals new insights into connectome dysfunctions in ADHD
Kanhao Zhao, Boris Duka, Hua Xie, et al.
NeuroImage (2021) Vol. 246, pp. 118774-118774
Open Access | Times Cited: 94
Deep learning for brain disorder diagnosis based on fMRI images
Wutao Yin, Longhai Li, Fang‐Xiang Wu
Neurocomputing (2020) Vol. 469, pp. 332-345
Closed Access | Times Cited: 86
Using DeepGCN to identify the autism spectrum disorder from multi-site resting-state data
Menglin Cao, Ming–Hsuan Yang, Chi Qin, et al.
Biomedical Signal Processing and Control (2021) Vol. 70, pp. 103015-103015
Closed Access | Times Cited: 83
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
Going deep into schizophrenia with artificial intelligence
Jose Cortes-Briones, Nicolas I. Tapia, Deepak Cyril D’Souza, et al.
Schizophrenia Research (2021) Vol. 245, pp. 122-140
Open Access | Times Cited: 70
A deep learning based model using RNN-LSTM for the Detection of Schizophrenia from EEG data
Rinku Supakar, Parthasarathi Satvaya, Prąsun Chakrabarti
Computers in Biology and Medicine (2022) Vol. 151, pp. 106225-106225
Closed Access | Times Cited: 55
Deep Learning in Neuroimaging: Promises and challenges
Weizheng Yan, Gang Qu, Wenxing Hu, et al.
IEEE Signal Processing Magazine (2022) Vol. 39, Iss. 2, pp. 87-98
Open Access | Times Cited: 50
SSPNet: An interpretable 3D-CNN for classification of schizophrenia using phase maps of resting-state complex-valued fMRI data
Qiu‐Hua Lin, Yan‐Wei Niu, Jing Sui, et al.
Medical Image Analysis (2022) Vol. 79, pp. 102430-102430
Open Access | Times Cited: 39
Unraveling overoptimism and publication bias in ML-driven science
Pouria Saidi, Gautam Dasarathy, Visar Berisha
Patterns (2025) Vol. 6, Iss. 4, pp. 101185-101185
Open Access | Times Cited: 1
Deep learning of brain magnetic resonance images: A brief review
Xingzhong Zhao, Xing‐Ming Zhao
Methods (2020) Vol. 192, pp. 131-140
Closed Access | Times Cited: 58
Artificial intelligence with deep learning in nuclear medicine and radiology
Milan Decuyper, Jens Maebe, Roel Van Holen, et al.
EJNMMI Physics (2021) Vol. 8, Iss. 1
Open Access | Times Cited: 47
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: 44
Mapping relationships among schizophrenia, bipolar and schizoaffective disorders: A deep classification and clustering framework using fMRI time series
Weizheng Yan, Min Zhao, Zening Fu, et al.
Schizophrenia Research (2021) Vol. 245, pp. 141-150
Open Access | Times Cited: 43
An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data
Min Zhao, Weizheng Yan, Na Luo, et al.
Medical Image Analysis (2022) Vol. 78, pp. 102413-102413
Open Access | Times Cited: 35
Towards artificial intelligence in mental health: a comprehensive survey on the detection of schizophrenia
Ashima Tyagi, Vibhav Prakash Singh, Manoj Madhava Gore
Multimedia Tools and Applications (2022) Vol. 82, Iss. 13, pp. 20343-20405
Closed Access | Times Cited: 29
Deep learning in neuroimaging data analysis: Applications, challenges, and solutions
Lev Kiar Avberšek, Grega Repovš
Frontiers in Neuroimaging (2022) Vol. 1
Open Access | Times Cited: 29
Machine learning techniques for the Schizophrenia diagnosis: a comprehensive review and future research directions
Shradha Verma, Tripti Goel, M. Tanveer, et al.
Journal of Ambient Intelligence and Humanized Computing (2023) Vol. 14, Iss. 5, pp. 4795-4807
Open Access | Times Cited: 21
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