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Finite Element Analysis

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A holistic physics-informed neural network solution for precise destruction of breast tumors using focused ultrasound on a realistic breast model.

Mathematical biosciences and engineering : MBE
This study presented a novel approach for the precise ablation of breast tumors using focused ultrasound (FUS), leveraging a physics-informed neural network (PINN) integrated with a realistic breast model. FUS has shown significant promise in treatin...

Implementing the discontinuous-Galerkin finite element method using graph neural networks with application to diffusion equations.

Neural networks : the official journal of the International Neural Network Society
Machine learning (ML) has benefited from both software and hardware advancements, leading to increasing interest in capitalising on ML throughout academia and industry. There have been efforts in the scientific computing community to leverage this de...

Super-fast and accurate nonlinear foot deformation Prediction using graph neural networks.

Journal of the mechanical behavior of biomedical materials
Recently, there has been a significant increase in the number of foot diseases, highlighting the importance of non-surgical treatments. Customized insoles, tailored to an individual's foot morphology, have emerged as a promising solution. However, th...

A bio-lattice deep learning framework for modeling discrete biological materials.

Journal of the mechanical behavior of biomedical materials
Biological tissues dynamically adapt their mechanical properties at the microscale in response to stimuli, often governed by discrete interacting mechanisms that dictate the material's behavior at the macroscopic scale. An approach to model the discr...

Predicting fall parameters from infant skull fractures using machine learning.

Biomechanics and modeling in mechanobiology
When infants are admitted to the hospital with skull fractures, providers must distinguish between cases of accidental and abusive head trauma. Limited information about the incident is available in such cases, and witness statements are not always r...

Machine learning and statistical shape modelling for real-time prediction of stent deployment in realistic anatomies.

Computer methods and programs in biomedicine
The rise in minimally invasive procedures has created a demand for efficient and reliable planning software to predict intra- and post-operative outcomes. Surrogate modelling has shown promise, but challenges remain, particularly in cardiovascular ap...

Neural network surrogate and projected gradient descent for fast and reliable finite element model calibration: A case study on an intervertebral disc.

Computers in biology and medicine
Accurate calibration of finite element (FE) models is essential across various biomechanical applications, including human intervertebral discs (IVDs), to ensure their reliability and use in diagnosing and planning treatments. However, traditional ca...

Machine learning models based on FEM simulation of hoop mode vibrations to enable ultrasonic cuffless measurement of blood pressure.

Medical & biological engineering & computing
Blood pressure (BP) is one of the vital physiological parameters, and its measurement is done routinely for almost all patients who visit hospitals. Cuffless BP measurement has been of great research interest over the last few years. In this paper, w...

Machine learning based finite element analysis for personalized prediction of pressure injury risk in patients with spinal cord injury.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Patients with spinal cord injury (SCI), are prone to pressure injury (PI) in the soft tissues of buttocks. Early prediction of PI holds the potential to reduce the occurrence and progression of PI. This study proposes a mach...

Inspired by the growth behavior of plants: biomimetic soft robots that just meet the requirements of use.

Bioinspiration & biomimetics
Soft robots are usually manufactured using the pouring method and can only be configured with a fixed execution area, which often faces the problem of insufficient or wasteful performance in real-world applications, and cannot be reused for other tas...