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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:

Deep learning-based hemodynamic prediction of carotid artery stenosis before and after surgical treatments
Sirui Wang, Dandan Wu, Gaoyang Li, et al.
Frontiers in Physiology (2023) Vol. 13
Open Access | Times Cited: 19

Showing 19 citing articles:

Physics-informed neural networks (PINNs) for 4D hemodynamics prediction: An investigation of optimal framework based on vascular morphology
Xuelan Zhang, Baoyan Mao, Yue Che, et al.
Computers in Biology and Medicine (2023) Vol. 164, pp. 107287-107287
Open Access | Times Cited: 25
Quantifying Carotid Stenosis: History, Current Applications, Limitations, and Potential: How Imaging Is Changing the Scenario
Luca Saba, Roberta Scicolone, Elias Johansson, et al.
Life (2024) Vol. 14, Iss. 1, pp. 73-73
Open Access | Times Cited: 7
3D printing of personalised stents using new advanced photopolymerizable resins and Ti-6Al-4V alloy
Diana-Irinel Băilă, Filippo Sanfilippo, Tom Savu, et al.
Rapid Prototyping Journal (2024) Vol. 30, Iss. 4, pp. 696-710
Closed Access | Times Cited: 5
Pulse wave-based evaluation of the blood-supply capability of patients with heart failure via machine learning
Sirui Wang, Ryohei Ono, Dandan Wu, et al.
BioMedical Engineering OnLine (2024) Vol. 23, Iss. 1
Open Access | Times Cited: 4
Deep learning-based real-time prediction of coronary artery blood flow pressure from computed tomography angiography
Yang Yang, Bao Li, Chuanqi Wen, et al.
Physics of Fluids (2025) Vol. 37, Iss. 2
Closed Access
Prediction of time averaged wall shear stress distribution in coronary arteries’ bifurcation varying in morphological features via deep learning
Mohammad Hossein Sarkhosh, Hadis Edrisnia, Mohammad Reza Raveshi, et al.
Frontiers in Physiology (2025) Vol. 16
Open Access
Non-invasive fractional flow reserve estimation in coronary arteries using angiographic images
Hadis Edrisnia, Mohammad Hossein Sarkhosh, Bahram Mohebbi, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
Unveiling hemodynamic pulsatile flow dynamics in carotid artery stenosis: Insights from computational fluid dynamics
Noureddine Kaid, Leila Benyamina, Younes Menni, et al.
AIP Advances (2024) Vol. 14, Iss. 6
Open Access | Times Cited: 2
Stenosis severity and heart rate effects on left coronary artery hemodynamics and myocardial oxygen balance: A comprehensive assessment using pressure gradient
Pawan Kumar, Somnath Roy, Prasanta Kumar Das
Physics of Fluids (2024) Vol. 36, Iss. 2
Open Access | Times Cited: 2
LAFlowNet: A dynamic graph method for the prediction of velocity and pressure fields in left atrium and left atrial appendage
Xiaoyu Liu, Hongtao Lin, Xingli Liu, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 136, pp. 108896-108896
Closed Access | Times Cited: 2
Four-dimensional hemodynamic prediction of abdominal aortic aneurysms following endovascular aneurysm repair combining physics-informed PointNet and quadratic residual networks
Jiaheng Kang, Gaoyang Li, Yue Che, et al.
Physics of Fluids (2024) Vol. 36, Iss. 8
Closed Access | Times Cited: 1
The calculation method of blood flow pressure based on four-dimensional flow magnetic resonance imaging and deep learning
C. Tao, Yanjing Han, Tianming Du, et al.
Physics of Fluids (2024) Vol. 36, Iss. 9
Closed Access | Times Cited: 1
Prediction of Hemodynamic-Related Hemolysis in Carotid Stenosis and Aiding in Treatment Planning and Risk Stratification Using Computational Fluid Dynamics
Krystian Jędrzejczak, Wojciech Orciuch, Krzysztof Wojtas, et al.
Biomedicines (2023) Vol. 12, Iss. 1, pp. 37-37
Open Access | Times Cited: 3
Quantile Loss Function Empowered Machine Learning Models for Predicting Carotid Arterial Blood Flow Characteristics
T. Raja Rani, Woshan Srimal, Abdullah Al Shibli, et al.
WSEAS TRANSACTIONS ON BIOLOGY AND BIOMEDICINE (2023) Vol. 20, pp. 155-170
Open Access | Times Cited: 2
The study of DIEA three dimensional reconstruction technique based on CTA in preoperative perforator selection
C.-L. Su, Han Yan, Shu Wang, et al.
Journal of Plastic Reconstructive & Aesthetic Surgery (2024) Vol. 90, pp. 189-191
Closed Access
Hemodynamic Analysis of Carotid Sinus with OpenFOAM and Machine Learning
Murad Kucur, Banu Körbahti, Ozan Onur Balkanay
IntechOpen eBooks (2024)
Open Access
Pulse wave signal-driven machine learning for identifying left ventricular enlargement in heart failure patients
Dandan Wu, Ryohei Ono, Sirui Wang, et al.
BioMedical Engineering OnLine (2024) Vol. 23, Iss. 1
Open Access
HARNESSING THE POWER OF ARTIFICIAL INTELLIGENCE TO REVOLUTIONIZE VASCULAR SURGERY: A COMPREHENSIVE REVIEW OF CURRENT APPLICATIONS, PROSPECTS, AND POTENTIAL CHALLENGES
Rodolpho Bicalho Bento, Breno Oliveira Gois, Nádia Oliveira Cabral, et al.
Revista Ibero-Americana de Humanidades, Ciências e Educação (2024) Vol. 10, Iss. 8, pp. 1256-1264
Open Access
Active Machine Learning for Pre-procedural Prediction of Time-Varying Boundary Condition After Fontan Procedure Using Generative Adversarial Networks
Wenyuan Song, David Frakes, Lakshmi Prasad Dasi
Annals of Biomedical Engineering (2024)
Closed Access
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