International Journal for Numerical Methods in Biomedical Engineering

Papers
(The H4-Index of International Journal for Numerical Methods in Biomedical Engineering is 16. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-04-01 to 2024-04-01.)
ArticleCitations
Persistent spectral graph44
Polygonal surface processing and mesh generation tools for the numerical simulation of the cardiac function37
Biomechanical modeling of novel high expansion auxetic skin grafts34
A 3D‐1D coupled blood flow and oxygen transport model to generate microvascular networks25
Biomechanical behaviour of temporomandibular joints during opening and closing of the mouth: A 3D finite element analysis25
A mathematical model that integrates cardiac electrophysiology, mechanics, and fluid dynamics: Application to the human left heart25
Automated generation of 0D and 1D reduced‐order models of patient‐specific blood flow24
Transitional turbulent flow in a stenosed coronary artery with a physiological pulsatile flow23
The effects of clinically‐derived parametric data uncertainty in patient‐specific coronary simulations with deformable walls21
Non‐Newtonian blood rheology impacts left atrial stasis in patient‐specific simulations20
Utilization of image interpolation and fusion in brain tumor segmentation19
Enabling forward uncertainty quantification and sensitivity analysis in cardiac electrophysiology by reduced order modeling and machine learning18
Cerebrospinal fluid dynamics coupled to the global circulation in holistic setting: Mathematical models, numerical methods and applications18
A method for the automatic detection of myopia in Optos fundus images based on deep learning18
Functional link convolutional neural network for the classification of diabetes mellitus16
Fluid flow‐induced cell stimulation in bone tissue engineering changes due to interstitial tissue formation in vitro16
Analysis of digitalized ECG signals based on artificial intelligence and spectral analysis methods specialized in ARVC16
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