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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:

Diagnostic Classification and Prognostic Prediction Using Common Genetic Variants in Autism Spectrum Disorder: Genotype-Based Deep Learning
Haishuai Wang, Paul Avillach
JMIR Medical Informatics (2021) Vol. 9, Iss. 4, pp. e24754-e24754
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

Revolutionizing healthcare: the role of artificial intelligence in clinical practice
Shuroug A. Alowais, Sahar S. Alghamdi, Nada Alsuhebany, et al.
BMC Medical Education (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 967
Deep learning for neurodegenerative disorder (2016 to 2022): A systematic review
Jyotismita Chaki, Marcin Woźniak
Biomedical Signal Processing and Control (2022) Vol. 80, pp. 104223-104223
Closed Access | Times Cited: 51
Triage and priority-based healthcare diagnosis using artificial intelligence for autism spectrum disorder and gene contribution: A systematic review
Shahad Sabbar Joudar, A. S. Albahri, Rula A. Hamid
Computers in Biology and Medicine (2022) Vol. 146, pp. 105553-105553
Open Access | Times Cited: 39
Neuroimaging genetics approaches to identify new biomarkers for the early diagnosis of autism spectrum disorder
Sabah Nisar, Mohammad Haris
Molecular Psychiatry (2023) Vol. 28, Iss. 12, pp. 4995-5008
Open Access | Times Cited: 24
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
Aythem Khairi Kareem, Mohammed M AL-Ani, Ahmed Adil Nafea
Baghdad Science Journal (2023) Vol. 20, Iss. 3(Suppl.), pp. 1182-1182
Open Access | Times Cited: 22
Bringing machine learning to research on intellectual and developmental disabilities: taking inspiration from neurological diseases
Chirag Gupta, Pramod Chandrashekar, Ting Jin, et al.
Journal of Neurodevelopmental Disorders (2022) Vol. 14, Iss. 1
Open Access | Times Cited: 31
Predicting the Epidemics Trend of COVID-19 Using Epidemiological-Based Generative Adversarial Networks
Haishuai Wang, Guangyu Tao, Jiali Ma, et al.
IEEE Journal of Selected Topics in Signal Processing (2022) Vol. 16, Iss. 2, pp. 276-288
Closed Access | Times Cited: 29
Review: Cancer and neurodevelopmental disorders: multi-scale reasoning and computational guide
Ruth Nussinov, Bengi Ruken Yavuz, Habibe Cansu Demirel, et al.
Frontiers in Cell and Developmental Biology (2024) Vol. 12
Open Access | Times Cited: 6
Detecting autism in children through drawing characteristics using the visual-motor integration test
P.S. Chen, Jasin Wong, Eva E. Chen, et al.
Health Information Science and Systems (2025) Vol. 13, Iss. 1
Closed Access
Bridging the Digital Divide: A Practical Roadmap for Deploying Medical Artificial Intelligence Technologies in Low-Resource Settings
Evelyn Wong, Alvaro Bermudez-Cañete, Matthew Campbell, et al.
Population Health Management (2025)
Closed Access
Machine-Learning Model for Genetic Disorder Prediction
Vanashree Agnihotri, Prathamesh Hire, Vaishali Ingle, et al.
Lecture notes in networks and systems (2025), pp. 133-144
Closed Access
Exploring Filipino Medical Students’ Attitudes and Perceptions of Artificial Intelligence in Medical Education: A Mixed-Methods Study
Robbi Miguel G. Falcon, Renne Margaret U. Alcazar, Hannah G. Babaran, et al.
MedEdPublish (2025) Vol. 14, pp. 282-282
Open Access
RLDS: An explainable residual learning diagnosis system for fetal congenital heart disease
Sibo Qiao, Shanchen Pang, Gang Luo, et al.
Future Generation Computer Systems (2021) Vol. 128, pp. 205-218
Closed Access | Times Cited: 31
A Pseudo-Siamese Feature Fusion Generative Adversarial Network for Synthesizing High-Quality Fetal Four-Chamber Views
Sibo Qiao, Silin Pan, Gang Luo, et al.
IEEE Journal of Biomedical and Health Informatics (2022) Vol. 27, Iss. 3, pp. 1193-1204
Closed Access | Times Cited: 21
A Deep Learning Approach for the Estimation of Glomerular Filtration Rate
Haishuai Wang, Benjamin Bowe, Zhicheng Cui, et al.
IEEE Transactions on NanoBioscience (2022) Vol. 21, Iss. 4, pp. 560-569
Closed Access | Times Cited: 19
Deep learning approach to predict autism spectrum disorder: a systematic review and meta-analysis
Yang Ding, Heng Zhang, Ting Qiu
BMC Psychiatry (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 3
FLDS: An Intelligent Feature Learning Detection System for Visualizing Medical Images Supporting Fetal Four-Chamber Views
Sibo Qiao, Shanchen Pang, Gang Luo, et al.
IEEE Journal of Biomedical and Health Informatics (2021) Vol. 26, Iss. 10, pp. 4814-4825
Closed Access | Times Cited: 26
The Sensory Abnormality Mediated Partially the Efficacy of Repetitive Transcranial Magnetic Stimulation on Treating Comorbid Sleep Disorder in Autism Spectrum Disorder Children
Lei Gao, Chen Wang, Xiao-rong Song, et al.
Frontiers in Psychiatry (2022) Vol. 12
Open Access | Times Cited: 12
Genomic Machine Learning Meta-regression: Insights on Associations of Study Features With Reported Model Performance
Eric J. Barnett, Daniel G. Onete, Asif Salekin, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2023) Vol. 21, Iss. 1, pp. 169-177
Open Access | Times Cited: 7
DeepASD: a deep adversarial-regularized graph learning method for ASD diagnosis with multimodal data
W.F. Chen, Jianjun Yang, Zhongquan Sun, et al.
Translational Psychiatry (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
Genomic Machine Learning Meta-regression: Insights on Associations of Study Features with Reported Model Performance
Eric J. Barnett, Daniel G. Onete, Asif Salekin, et al.
medRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 9
Beyond radiologist-level liver lesion detection on multi-phase contrast-enhanced CT images by deep learning
Lei Wu, Haishuai Wang, Yining Chen, et al.
iScience (2023) Vol. 26, Iss. 11, pp. 108183-108183
Open Access | Times Cited: 5
Graph Node Classification to Predict Autism Risk in Genes
Danushka Bandara, Kyle Riccardi
Genes (2024) Vol. 15, Iss. 4, pp. 447-447
Open Access | Times Cited: 1
Seeing beyond words: Visualizing autism spectrum disorder biomarker insights
Xinyue Xie, Rongyi Zhou, Zihan Fang, et al.
Heliyon (2024) Vol. 10, Iss. 9, pp. e30420-e30420
Open Access | Times Cited: 1
A deep learning model for prediction of autism status using whole-exome sequencing data
Qing Wu, Eric M. Morrow, Ece D. Gamsiz Uzun
PLoS Computational Biology (2024) Vol. 20, Iss. 11, pp. e1012468-e1012468
Open Access | Times Cited: 1
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