AIMC Topic: Computer Simulation

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Forecasting and Predicting Stochastic Agent-Based Model Data with Biologically-Informed Neural Networks.

Bulletin of mathematical biology Sep 23, 2024
Collective migration is an important component of many biological processes, including wound healing, tumorigenesis, and embryo development. Spatial agent-based models (ABMs) are often used to model collective migration, but it is challenging to thor...
Neural Networks, Computer Forecasting Computer Simulation Animals Cell Movement Humans Mathematical Concepts Models, Biological Systems Analysis Stochastic Processes Dictyostelium
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Spectral integrated neural networks (SINNs) for solving forward and inverse dynamic problems.

Neural networks : the official journal of the International Neural Network Society Sep 22, 2024
This study introduces an innovative neural network framework named spectral integrated neural networks (SINNs) to address both forward and inverse dynamic problems in three-dimensional space. In the SINNs, the spectral integration technique is utiliz...
Neural Networks, Computer Algorithms Computer Simulation Nonlinear Dynamics
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Physics-Informed Graph Neural Networks to solve 1-D equations of blood flow.

Computer methods and programs in biomedicine Sep 20, 2024
BACKGROUND AND OBJECTIVE: Computational models of hemodynamics can contribute to optimizing surgical plans, and improve our understanding of cardiovascular diseases. Recently, machine learning methods have become essential to reduce the computational...
Models, Cardiovascular Machine Learning Arteries Algorithms Humans Hemodynamics Computer Simulation Blood Flow Velocity Neural Networks, Computer
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Prediction of directional solidification in freeze casting of biomaterial scaffolds using physics-informed neural networks.

Biomedical physics & engineering express Sep 20, 2024
Freeze casting, a manufacturing technique widely applied in biomedical fields for fabricating biomaterial scaffolds, poses challenges for predicting directional solidification due to its highly nonlinear behavior and complex interplay of process para...
Neural Networks, Computer Algorithms Computer Simulation Humans Tissue Scaffolds Freezing Temperature Hydrodynamics Biocompatible Materials Tissue Engineering
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Real-Time Calibration-Free Musculotendon Kinematics for Neuromusculoskeletal Models.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 20, 2024
Neuromusculoskeletal (NMS) models enable non-invasive estimation of clinically important internal biomechanics. A critical part of NMS modelling is the estimation of musculotendon kinematics, which comprise musculotendon unit lengths, moment arms, an...
Models, Biological Adult Algorithms Biomechanical Phenomena Computer Simulation Calibration Humans Male Female Neural Networks, Computer Computer Systems Muscle, Skeletal
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Coagulo-Net: Enhancing the mathematical modeling of blood coagulation using physics-informed neural networks.

Neural networks : the official journal of the International Neural Network Society Sep 19, 2024
Blood coagulation, which involves a group of complex biochemical reactions, is a crucial step in hemostasis to stop bleeding at the injury site of a blood vessel. Coagulation abnormalities, such as hypercoagulation and hypocoagulation, could either c...
Humans Neural Networks, Computer Computer Simulation Models, Theoretical Blood Coagulation
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Deep learning-enabled fluorescence imaging for surgical guidance: training for oral cancer depth quantification.

Journal of biomedical optics Sep 18, 2024
SIGNIFICANCE: Oral cancer surgery requires accurate margin delineation to balance complete resection with post-operative functionality. Current fluorescence imaging systems provide two-dimensional margin assessment yet fail to quantify tumor depth p...
Mouth Neoplasms Optical Imaging Phantoms, Imaging Margins of Excision Deep Learning Image Processing, Computer-Assisted Surgery, Computer-Assisted Neural Networks, Computer Computer Simulation Humans
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FGTN: Fragment-based graph transformer network for predicting reproductive toxicity.

Archives of toxicology Sep 18, 2024
Reproductive toxicity is one of the important issues in chemical safety. Traditional laboratory testing methods are costly and time-consuming with raised ethical issues. Only a few in silico models have been reported to predict human reproductive tox...
Reproduction Quantitative Structure-Activity Relationship Toxicity Tests Neural Networks, Computer Computer Simulation Humans
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Physiological control for left ventricular assist devices based on deep reinforcement learning.

Artificial organs Sep 17, 2024
BACKGROUND: The improvement of controllers of left ventricular assist device (LVAD) technology supporting heart failure (HF) patients has enormous impact, given the high prevalence and mortality of HF in the population. The use of reinforcement learn...
Ventricular Function, Left Hemodynamics Deep Learning Humans Algorithms Computer Simulation Models, Cardiovascular Heart Failure Heart-Assist Devices
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In Silico Insights: QSAR Modeling of TBK1 Kinase Inhibitors for Enhanced Drug Discovery.

Journal of chemical information and modeling Sep 17, 2024
TBK1, or TANK-binding kinase 1, is an enzyme that functions as a serine/threonine protein kinase. It plays a crucial role in various cellular processes, including the innate immune response to viruses, cell proliferation, apoptosis, autophagy, and an...
Protein Kinase Inhibitors Computer Simulation Drug Discovery Protein Serine-Threonine Kinases Models, Molecular Humans Quantitative Structure-Activity Relationship Machine Learning
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