AIMC Topic: Models, Cardiovascular
Clear Filters Showing 31 to 40 of 154 articles
Modeling 3D Cardiac Contraction and Relaxation With Point Cloud Deformation Networks.
IEEE journal of biomedical and health informatics
Aug 6, 2024
Global single-valued biomarkers, such as ejection fraction, are widely used in clinical practice to assess cardiac function. However, they only approximate the heart's true 3D deformation process, thus limiting diagnostic accuracy and the understandi...
Noninvasive and fast method of calculation for instantaneous wave-free ratio based on haemodynamics and deep learning.
Computer methods and programs in biomedicine
Jul 23, 2024
BACKGROUND AND OBJECTIVES: Instantaneous wave-free ratio (iFR) is a new invasive indicator of myocardial ischaemia, and its diagnostic performance is as good as the "gold standard" of myocardial ischaemia diagnosis: fractional flow reserve (FFR). iFR...
Unsupervised stochastic learning and reduced order modeling for global sensitivity analysis in cardiac electrophysiology models.
Computer methods and programs in biomedicine
Jul 8, 2024
BACKGROUND AND OBJECTIVE: Numerical simulations in electrocardiology are often affected by various uncertainties inherited from the lack of precise knowledge regarding input values including those related to the cardiac cell model, domain geometry, a...
Review of Machine Learning Techniques in Soft Tissue Biomechanics and Biomaterials.
Cardiovascular engineering and technology
Jul 2, 2024
BACKGROUND AND OBJECTIVE: Advanced material models and material characterization of soft biological tissues play an essential role in pre-surgical planning for vascular surgeries and transcatheter interventions. Recent advances in heart valve enginee...
Modeling of valve-in-valve transcatheter aortic valve implantation after aortic root replacement using a 3-dimensional artificial intelligence algorithm.
The Journal of thoracic and cardiovascular surgery
Jun 29, 2024
OBJECTIVE: Aortic root replacement requires construction of a composite valve-graft and reimplantation of coronary arteries. This study assessed the feasibility of valve-in-valve transcatheter aortic valve implantation after aortic root replacement.
Models, Cardiovascular
Transcatheter Aortic Valve Replacement
Bioprosthesis
Feasibility Studies
Heart Valve Prosthesis
Computed Tomography Angiography
Aged, 80 and over
Retrospective Studies
Humans
Male
Female
Artificial Intelligence
Treatment Outcome
Imaging, Three-Dimensional
Aged
Algorithms
Aortic Valve
Prosthesis Design
Image2Flow: A proof-of-concept hybrid image and graph convolutional neural network for rapid patient-specific pulmonary artery segmentation and CFD flow field calculation from 3D cardiac MRI data.
PLoS computational biology
Jun 20, 2024
Computational fluid dynamics (CFD) can be used for non-invasive evaluation of hemodynamics. However, its routine use is limited by labor-intensive manual segmentation, CFD mesh creation, and time-consuming simulation. This study aims to train a deep ...
Physics-informed neural networks for parameter estimation in blood flow models.
Computers in biology and medicine
Jun 5, 2024
BACKGROUND: Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving inverse problems, especially in cases where no complete information about the system is known and scatter measurements are available. This is especially ...
Exploring a new frontier in cardiac diagnosis: ECG analysis enhanced by machine learning and parametric quartic spline modeling.
Journal of electrocardiology
May 21, 2024
The heart's study holds paramount importance in human physiology, driving valuable research in cardiovascular health. However, assessing Electrocardiogram (ECG) analysis techniques poses challenges due to noise and artifacts in authentic recordings. ...
Deep-learning-based real-time individualization for reduce-order haemodynamic model.
Computers in biology and medicine
Apr 15, 2024
The reduced-order lumped parameter model (LPM) has great computational efficiency in real-time numerical simulations of haemodynamics but is limited by the accuracy of patient-specific computation. This study proposed a method to achieve the individu...
Sensitivity analysis of the mechanical properties on atherosclerotic arteries rupture risk with an artificial neural network method.
Computer methods in biomechanics and biomedical engineering
Jan 25, 2024
Considering the differences between individuals, in this paper, an uncertainty analysis model for predicting rupture risk of atherosclerotic arteries is established based on a back-propagation artificial neural network. The influence of isotropy and ...
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