AIMC Topic:
Computer Simulation

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Biologically-informed neural networks guide mechanistic modeling from sparse experimental data.

PLoS computational biology Dec 1, 2020
Biologically-informed neural networks (BINNs), an extension of physics-informed neural networks [1], are introduced and used to discover the underlying dynamics of biological systems from sparse experimental data. In the present work, BINNs are train...
Machine Learning Computer Simulation Nonlinear Dynamics Neural Networks, Computer
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Retrospective respiratory motion correction in cardiac cine MRI reconstruction using adversarial autoencoder and unsupervised learning.

NMR in biomedicine Nov 30, 2020
The aim of this study was to develop a deep neural network for respiratory motion compensation in free-breathing cine MRI and evaluate its performance. An adversarial autoencoder network was trained using unpaired training data from healthy volunteer...
Magnetic Resonance Imaging, Cine Statistics, Nonparametric Breath Holding Neural Networks, Computer Humans Unsupervised Machine Learning Artifacts Motion Computer Simulation Heart Respiration Image Processing, Computer-Assisted
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Adaptive Tracking Control of State Constraint Systems Based on Differential Neural Networks: A Barrier Lyapunov Function Approach.

IEEE transactions on neural networks and learning systems Nov 30, 2020
The aim of this article is to investigate the trajectory tracking problem of systems with uncertain models and state restrictions using differential neural networks (DNNs). The adaptive control design considers the design of a nonparametric identifie...
Neural Networks, Computer Algorithms Uncertainty Robotics Nonlinear Dynamics Finite Element Analysis Computer Simulation Models, Theoretical
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Unsupervised AER Object Recognition Based on Multiscale Spatio-Temporal Features and Spiking Neurons.

IEEE transactions on neural networks and learning systems Nov 30, 2020
This article proposes an unsupervised address event representation (AER) object recognition approach. The proposed approach consists of a novel multiscale spatio-temporal feature (MuST) representation of input AER events and a spiking neural network ...
Models, Neurological Humans Neurons Artificial Intelligence Algorithms Pattern Recognition, Automated Electronic Data Processing Neural Networks, Computer Databases, Factual Computer Simulation
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A new deep learning method for displacement tracking from ultrasound RF signals of vascular walls.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Nov 24, 2020
It is necessary to monitor the mechanical properties of arteries which directly related to cardiovascular diseases (CVDs) in the early stages. In this study, we proposed a new method based on deep learning (DL) to track the displacement of the vessel...
Radio Waves Computer Simulation Ultrasonography Deep Learning Arteries
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A User-Oriented Intelligent Access Selection Algorithm in Heterogeneous Wireless Networks.

Computational intelligence and neuroscience Nov 24, 2020
A heterogeneous wireless network (HWN) contains many kinds of wireless networks with overlapping areas of signal coverage. One of the research topics on HWNs is how to make users choose the most suitable network. This paper designs a user-oriented in...
Fuzzy Logic Computer Simulation Neural Networks, Computer Learning Algorithms
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A random forest based biomarker discovery and power analysis framework for diagnostics research.

BMC medical genomics Nov 23, 2020
BACKGROUND: Biomarker identification is one of the major and important goal of functional genomics and translational medicine studies. Large scale -omics data are increasingly being accumulated and can provide vital means for the identification of bi...
Machine Learning Workflow Algorithms Lipidomics Computer Simulation Molecular Diagnostic Techniques Humans Regression Analysis Biomarkers Transcriptome Metabolomics Datasets as Topic Decision Trees Sample Size
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FBP-Net for direct reconstruction of dynamic PET images.

Physics in medicine and biology Nov 20, 2020
Dynamic positron emission tomography (PET) imaging can provide information about metabolic changes over time, used for kinetic analysis and auxiliary diagnosis. Existing deep learning-based reconstruction methods have too many trainable parameters an...
Neural Networks, Computer Algorithms Positron-Emission Tomography Computer Simulation Kinetics
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Methods for correcting inference based on outcomes predicted by machine learning.

Proceedings of the National Academy of Sciences of the United States of America Nov 18, 2020
Many modern problems in medicine and public health leverage machine-learning methods to predict outcomes based on observable covariates. In a wide array of settings, predicted outcomes are used in subsequent statistical analysis, often without accoun...
Organ Specificity Computer Simulation Cause of Death Humans Machine Learning
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DNN-assisted statistical analysis of a model of local cortical circuits.

Scientific reports Nov 18, 2020
In neuroscience, computational modeling is an effective way to gain insight into cortical mechanisms, yet the construction and analysis of large-scale network models-not to mention the extraction of underlying principles-are themselves challenging ta...
Neurons Mammals Cerebral Cortex Models, Neurological Data Interpretation, Statistical Animals Logistic Models Neural Networks, Computer Computer Simulation
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