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Computer Simulation

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In silico prediction of ocular toxicity of compounds using explainable machine learning and deep learning approaches.

Journal of applied toxicology : JAT
The accurate identification of chemicals with ocular toxicity is of paramount importance in health hazard assessment. In contemporary chemical toxicology, there is a growing emphasis on refining, reducing, and replacing animal testing in safety evalu...

Residual current detection method based on improved VMD-BPNN.

PloS one
To further enhance the residual current detection capability of low-voltage distribution networks, an improved adaptive residual current detection method that combines variational modal decomposition (VMD) and BP neural network (BPNN) is proposed. Fi...

Prediction of Drug-Disease Associations Based on Multi-Kernel Deep Learning Method in Heterogeneous Graph Embedding.

IEEE/ACM transactions on computational biology and bioinformatics
Computational drug repositioning can identify potential associations between drugs and diseases. This technology has been shown to be effective in accelerating drug development and reducing experimental costs. Although there has been plenty of resear...

Validation of a Simulation Model for Robotic Myomectomy.

Journal of minimally invasive gynecology
STUDY OBJECTIVE: Several simulation models have been evaluated for gynecologic procedures such as hysterectomy, but there are limited published data for myomectomy. This study aimed to assess the validity of a low-cost robotic myomectomy model for su...

Hemodynamic factors of spontaneous vertebral artery dissecting aneurysms assessed with numerical and deep learning algorithms: Role of blood pressure and asymmetry.

Neuro-Chirurgie
BACKGROUND AND OBJECTIVES: The pathophysiology of spontaneous vertebral artery dissecting aneurysms (SVADA) is poorly understood. Our goal is to investigate the hemodynamic factors contributing to their formation using computational fluid dynamics (C...

Unsupervised motion artifact correction of turbo spin-echo MRI using deep image prior.

Magnetic resonance in medicine
PURPOSE: In MRI, motion artifacts can significantly degrade image quality. Motion artifact correction methods using deep neural networks usually required extensive training on large datasets, making them time-consuming and resource-intensive. In this...

Scalable Multi-Hierarchy Embedded Platform for Neural Population Simulations.

IEEE transactions on biomedical circuits and systems
Brain-inspired structured neural circuits are the cornerstones of both computational and perceived intelligence. Real-time simulations of large-scale high-dimensional neural populations with complex nonlinearities pose a significant challenge. Taking...

AutoMolDesigner for Antibiotic Discovery: An AI-Based Open-Source Software for Automated Design of Small-Molecule Antibiotics.

Journal of chemical information and modeling
Discovery of small-molecule antibiotics with novel chemotypes serves as one of the essential strategies to address antibiotic resistance. Although a considerable number of computational tools committed to molecular design have been reported, there is...

iDVEIP: A computer-aided approach for the prediction of viral entry inhibitory peptides.

Proteomics
With the notable surge in therapeutic peptide development, various peptides have emerged as potential agents against virus-induced diseases. Viral entry inhibitory peptides (VEIPs), a subset of antiviral peptides (AVPs), offer a promising avenue as e...

Designing optimal behavioral experiments using machine learning.

eLife
Computational models are powerful tools for understanding human cognition and behavior. They let us express our theories clearly and precisely and offer predictions that can be subtle and often counter-intuitive. However, this same richness and abili...