AIMC Topic: Computer Simulation
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Investigating the impact of initial parameters on autonomous robot swarm movement strategies for enhanced exploration efficiency: a comprehensive study.
Bioinspiration & biomimetics
Jun 12, 2024
Swarm robots are frequently preferred for the exploration of harsh environments and search and rescue operations. This study explores the factors that influence the movement strategies of autonomous robot swarms and their impact on swarm distribution...
Experiment-free exoskeleton assistance via learning in simulation.
Nature
Jun 12, 2024
Exoskeletons have enormous potential to improve human locomotive performance. However, their development and broad dissemination are limited by the requirement for lengthy human tests and handcrafted control laws. Here we show an experiment-free meth...
Res-TransNet: A Hybrid deep Learning Network for Predicting Pathological Subtypes of lung Adenocarcinoma in CT Images.
Journal of imaging informatics in medicine
Jun 11, 2024
This study aims to develop a CT-based hybrid deep learning network to predict pathological subtypes of early-stage lung adenocarcinoma by integrating residual network (ResNet) with Vision Transformer (ViT). A total of 1411 pathologically confirmed gr...
Assessing the anticholinergic cognitive burden classification of putative anticholinergic drugs using drug properties.
British journal of clinical pharmacology
Jun 11, 2024
AIMS: This study evaluated the use of machine learning to leverage drug absorption, distribution, metabolism and excretion (ADME) data together with physicochemical and pharmacological data to develop a novel anticholinergic burden scale and compare ...
Managing low-acuity patients in an Emergency Department through simulation-based multiobjective optimization using a neural network metamodel.
Health care management science
Jun 10, 2024
This paper deals with Emergency Department (ED) fast-tracks for low-acuity patients, a strategy often adopted to reduce ED overcrowding. We focus on optimizing resource allocation in minor injuries units, which are the ED units that can treat low-acu...
Emulator-Based Bayesian Calibration of the CISNET Colorectal Cancer Models.
Medical decision making : an international journal of the Society for Medical Decision Making
Jun 10, 2024
PURPOSE: To calibrate Cancer Intervention and Surveillance Modeling Network (CISNET)'s SimCRC, MISCAN-Colon, and CRC-SPIN simulation models of the natural history colorectal cancer (CRC) with an emulator-based Bayesian algorithm and internally valida...
ssVERDICT: Self-supervised VERDICT-MRI for enhanced prostate tumor characterization.
Magnetic resonance in medicine
Jun 9, 2024
PURPOSE: Demonstrating and assessing self-supervised machine-learning fitting of the VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumors) model for prostate cancer.
Diffusion Magnetic Resonance Imaging
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Least-Squares Analysis
Supervised Machine Learning
Image Interpretation, Computer-Assisted
Prostatic Neoplasms
Prostate
Male
Middle Aged
Deep Learning
Neural Networks, Computer
Algorithms
Computer Simulation
Humans
Enhanced parameter estimation in multiparametric arterial spin labeling using artificial neural networks.
Magnetic resonance in medicine
Jun 9, 2024
PURPOSE: Multiparametric arterial spin labeling (MP-ASL) can quantify cerebral blood flow (CBF) and arterial cerebral blood volume (CBV). However, its accuracy is compromised owing to its intrinsically low SNR, necessitating complex and time-consumin...
FetoML: Interpretable predictions of the fetotoxicity of drugs based on machine learning approaches.
Molecular informatics
Jun 8, 2024
Pregnant females may use medications to manage health problems that develop during pregnancy or that they had prior to pregnancy. However, using medications during pregnancy has a potential risk to the fetus. Assessing the fetotoxicity of drugs is es...
DDT-Net: Dose-Agnostic Dual-Task Transfer Network for Simultaneous Low-Dose CT Denoising and Simulation.
IEEE journal of biomedical and health informatics
Jun 6, 2024
Deep learning (DL) algorithms have achieved unprecedented success in low-dose CT (LDCT) imaging and are expected to be a new generation of CT reconstruction technology. However, most DL-based denoising models often lack the ability to generalize to u...
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