AIMC Topic: Computer Simulation
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Leveraging Extended Windows in End-to-End Deep Learning for Improved Continuous Myoelectric Locomotion Prediction.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 26, 2025
Current surface electromyography (sEMG) methods for locomotion mode prediction face limitations in anticipatory capability due to computation delays and constrained window lengths typically below 500 ms-a practice historically tied to stationarity re...
A Hybrid ODE-NN Framework for Modeling Incomplete Physiological Systems.
IEEE transactions on bio-medical engineering
Mar 21, 2025
This paper proposes a method to learn approximations of missing Ordinary Differential Equations (ODEs) and states in physiological models where knowledge of the system's relevant states and dynamics is incomplete. The proposed method augments known O...
A Review of In Silico Approaches for Discovering Natural Viral Protein Inhibitors in Aquaculture Disease Control.
Journal of fish diseases
Mar 20, 2025
Viral diseases pose a significant threat to the sustainability of global aquaculture, causing economic losses and compromising food security. Traditional control methods often demonstrate limited effectiveness, highlighting the need for alternative a...
Uncovering water conservation patterns in semi-arid regions through hydrological simulation and deep learning.
PloS one
Mar 20, 2025
Under the increasing pressure of global climate change, water conservation (WC) in semi-arid regions is experiencing unprecedented levels of stress. WC involves complex, nonlinear interactions among ecosystem components like vegetation, soil structur...
Risk assessment of potentially toxic elements and mapping of groundwater pollution indices using soft computer models in an agricultural area, Northeast Algeria.
Journal of hazardous materials
Mar 19, 2025
Groundwater (GW) quality and contamination by potentially toxic elements (PTEs) are major concerns for environmental sustainability, particularly in arid regions. The aim of this study was to assess the human health risks associated with GW contamina...
A novel seven-tier framework for the classification of MEFV missense variants using adaptive and rigid classifiers.
Scientific reports
Mar 17, 2025
There is a great discrepancy between the clinical categorization of MEFV gene variants and in silico tool predictions. In this study, we developed a seven-tier classification system for MEFV missense variants of unknown significance and recommended a...
Initial characterization of a novel dual-robot orthovoltage radiotherapy system.
Biomedical physics & engineering express
Mar 17, 2025
Adequate access to radiotherapy is a critical global concern affecting low-resource settings such as low- and middle-income countries and rural regions. We propose to reduce this disparity by developing a novel low-cost radiotherapy device that treat...
Understanding the Spatio-Temporal Coupling of Spikes and Spindles in Focal Epilepsy Through a Network-Level Computational Model.
International journal of neural systems
Mar 15, 2025
The electrophysiological findings have shown that epileptiform spikes triggering sleep spindles within 1[Formula: see text]s across multiple channels are commonly observed during sleep in focal epilepsy (FE). Such spatio-temporal couplings of spikes ...
Transcranial adaptive aberration correction using deep learning for phased-array ultrasound therapy.
Ultrasonics
Mar 14, 2025
This study aims to explore the feasibility of a deep learning approach to correct the distortion caused by the skull, thereby developing a transcranial adaptive focusing method for safe ultrasonic treatment in opening of the blood-brain barrier (BBB)...
A deep learning approach to multi-fiber parameter estimation and uncertainty quantification in diffusion MRI.
Medical image analysis
Mar 14, 2025
Diffusion MRI (dMRI) is the primary imaging modality used to study brain microstructure in vivo. Reliable and computationally efficient parameter inference for common dMRI biophysical models is a challenging inverse problem, due to factors such as va...
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