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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:

Personalising left-ventricular biophysical models of the heart using parametric physics-informed neural networks
Stefano Buoso, T. A. Joyce, Sebastian Kozerke
Medical Image Analysis (2021) Vol. 71, pp. 102066-102066
Open Access | Times Cited: 59

Showing 1-25 of 59 citing articles:

Uncovering near-wall blood flow from sparse data with physics-informed neural networks
Amirhossein Arzani, Jianxun Wang, Roshan M. D’Souza
Physics of Fluids (2021) Vol. 33, Iss. 7
Open Access | Times Cited: 193
Methods for enabling real-time analysis in digital twins: A literature review
Mohammad Sadegh Es-haghi, Cosmin Anitescu, Timon Rabczuk
Computers & Structures (2024) Vol. 297, pp. 107342-107342
Open Access | Times Cited: 19
Quantification of total uncertainty in the physics-informed reconstruction of CVSim-6 physiology
Mario De Florio, Zongren Zou, Daniele E. Schiavazzi, et al.
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences (2025) Vol. 383, Iss. 2292
Open Access | Times Cited: 2
Machine Learning for Cardiovascular Biomechanics Modeling: Challenges and Beyond
Amirhossein Arzani, Jianxun Wang, Michael S. Sacks, et al.
Annals of Biomedical Engineering (2022) Vol. 50, Iss. 6, pp. 615-627
Closed Access | Times Cited: 60
Physics-informed radial basis network (PIRBN): A local approximating neural network for solving nonlinear partial differential equations
Jinshuai Bai, Guirong Liu, Ashish Gupta, et al.
Computer Methods in Applied Mechanics and Engineering (2023) Vol. 415, pp. 116290-116290
Open Access | Times Cited: 34
Physics-informed graph neural network emulation of soft-tissue mechanics
David R. Dalton, Dirk Husmeier, Hao Gao
Computer Methods in Applied Mechanics and Engineering (2023) Vol. 417, pp. 116351-116351
Open Access | Times Cited: 24
Comprehensive review of deep learning in orthopaedics: Applications, challenges, trustworthiness, and fusion
Laith Alzubaidi, Khamael Al-Dulaimi, Asma Salhi, et al.
Artificial Intelligence in Medicine (2024) Vol. 155, pp. 102935-102935
Open Access | Times Cited: 10
Physics-Informed Computer Vision: A Review and Perspectives
Chayan Banerjee, Kien Nguyen, Clinton Fookes, et al.
ACM Computing Surveys (2024) Vol. 57, Iss. 1, pp. 1-38
Open Access | Times Cited: 9
CMRsim–A python package for cardiovascular MR simulations incorporating complex motion and flow
Jonathan Weine, Charles McGrath, Pietro Dirix, et al.
Magnetic Resonance in Medicine (2024) Vol. 91, Iss. 6, pp. 2621-2637
Open Access | Times Cited: 7
A neural network finite element approach for high speed cardiac mechanics simulations
Shruti Motiwale, Wenbo Zhang, Reese Feldmeier, et al.
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 427, pp. 117060-117060
Closed Access | Times Cited: 6
Machine learning and reduced order modelling for the simulation of braided stent deployment
Beatrice Bisighini, Miquel Aguirre, Marco Evangelos Biancolini, et al.
Frontiers in Physiology (2023) Vol. 14
Open Access | Times Cited: 14
Accelerated simulation methodologies for computational vascular flow modelling
Michael MacRaild, Ali Sarrami‐Foroushani, Toni Lassila, et al.
Journal of The Royal Society Interface (2024) Vol. 21, Iss. 211
Open Access | Times Cited: 5
Strategies for multi-case physics-informed neural networks for tube flows: a study using 2D flow scenarios
Hong Shen Wong, Wei Xuan Chan, Bing Huan Li, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 5
Machine learning and statistical shape modelling for real-time prediction of stent deployment in realistic anatomies
Beatrice Bisighini, Miquel Aguirre, Baptiste Pierrat, et al.
Computer Methods and Programs in Biomedicine (2025) Vol. 260, pp. 108583-108583
Open Access
Automatic analysis of 3D cardiac tagged magnetic resonance images using neural networks trained on synthetic data
Stefano Buoso, Christian T. Stoeck, Sebastian Kozerke
Journal of Cardiovascular Magnetic Resonance (2025), pp. 101869-101869
Open Access
Physics-informed neural network for load sway prediction in travelling autonomous mobile cranes
Zhuomin Zhou, Brandon Johns, Yihai Fang, et al.
Advanced Engineering Informatics (2025) Vol. 65, pp. 103269-103269
Open Access
A Neural Network Finite Element Trileaflet Heart Valve Model Incorporating Multi‐Body Contact
K. F. Meyer, Christian Goodbrake, Michael S. Sacks
International Journal for Numerical Methods in Biomedical Engineering (2025) Vol. 41, Iss. 4
Closed Access
Virtual Heart Therapy: Multiscale Models of Cardiac Disease Treatment and Recovery
Johane Bracamonte, Jeffrey W. Holmes
(2025), pp. 341-402
Closed Access
On the myocardium modeling under multimodal deformations: a comparison between costa’s, Holzapfel and Ogden’s formulations
Nicolás Laita, Miguel Ángel Martínez, M. Doblaré, et al.
Meccanica (2025)
Open Access
Explicit Physics-Informed Deep Learning for Computer-Aided Diagnostic Tasks in Medical Imaging
Shira Nemirovsky-Rotman, E. Bercovich
Machine Learning and Knowledge Extraction (2024) Vol. 6, Iss. 1, pp. 385-401
Open Access | Times Cited: 4
Sensitivity analysis and inverse uncertainty quantification for the left ventricular passive mechanics
Alan Lazarus, David R. Dalton, Dirk Husmeier, et al.
Biomechanics and Modeling in Mechanobiology (2022) Vol. 21, Iss. 3, pp. 953-982
Open Access | Times Cited: 16
Emulation of cardiac mechanics using Graph Neural Networks
David R. Dalton, Hao Gao, Dirk Husmeier
Computer Methods in Applied Mechanics and Engineering (2022) Vol. 401, pp. 115645-115645
Open Access | Times Cited: 16
Variable separated physics-informed neural networks based on adaptive weighted loss functions for blood flow model
Youqiong Liu, Li Cai, Yaping Chen, et al.
Computers & Mathematics with Applications (2023) Vol. 153, pp. 108-122
Closed Access | Times Cited: 9
Review of Machine Learning Techniques in Soft Tissue Biomechanics and Biomaterials
Samir Donmazov, Eda Nur Saruhan, Kerem Pekkan, et al.
Cardiovascular Engineering and Technology (2024) Vol. 15, Iss. 5, pp. 522-549
Closed Access | Times Cited: 3
Physics-informed neural network estimation of material properties in soft tissue nonlinear biomechanical models
Federica Caforio, Francesco Regazzoni, Stefano Pagani, et al.
Computational Mechanics (2024)
Open Access | Times Cited: 3
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