AIMC Topic: Computer Simulation

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Learned spatiotemporal correlation priors for CEST image denoising using incorporated global-spectral convolution neural network.

Magnetic resonance in medicine Jun 18, 2023
PURPOSE: To develop a deep learning-based method, dubbed Denoising CEST Network (DECENT), to fully exploit the spatiotemporal correlation prior to CEST image denoising.
Signal-To-Noise Ratio Phantoms, Imaging Mice Humans Neural Networks, Computer Algorithms Animals Computer Simulation Image Processing, Computer-Assisted
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Hemodynamic study of blood flow in the aorta during the interventional robot treatment using fluid-structure interaction.

Biomechanics and modeling in mechanobiology Jun 17, 2023
An interventional robot is a means for vascular diagnosis and treatment, and it can perform dredging, releasing drug and operating. Normal hemodynamic indicators are a prerequisite for the application of interventional robots. The current hemodynamic...
Computer Simulation Hemodynamics Robotics Blood Pressure Models, Cardiovascular Pulsatile Flow Blood Flow Velocity Aorta
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Deep Learning for Identifying Promising Drug Candidates in Drug-Phospholipid Complexes.

Molecules (Basel, Switzerland) Jun 16, 2023
Drug-phospholipid complexing is a promising formulation technology for improving the low bioavailability of active pharmaceutical ingredients (APIs). However, identifying whether phospholipid and candidate drug can form a complex through in vitro tes...
Computer Simulation Deep Learning Neural Networks, Computer Machine Learning Technology
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The comparison data forest: A new comparison data approach to determine the number of factors in exploratory factor analysis.

Behavior research methods Jun 15, 2023
Developing psychological assessment instruments often involves exploratory factor analyses, during which one must determine the number of factors to retain. Several factor-retention criteria have emerged that can infer this number from empirical data...
Machine Learning Humans Factor Analysis, Statistical Computer Simulation
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Bloch simulator-driven deep recurrent neural network for magnetization transfer contrast MR fingerprinting and CEST imaging.

Magnetic resonance in medicine Jun 15, 2023
PURPOSE: To develop a unified deep-learning framework by combining an ultrafast Bloch simulator and a semisolid macromolecular magnetization transfer contrast (MTC) MR fingerprinting (MRF) reconstruction for estimation of MTC effects.
Computer Simulation Image Processing, Computer-Assisted Magnetic Resonance Imaging Phantoms, Imaging Neural Networks, Computer Brain Humans
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Novel LKF Method on H Synchronization of Switched Time-Delay Systems.

IEEE transactions on cybernetics Jun 15, 2023
This article investigates H global asymptotic synchronization (GAS) of switched nonlinear systems with delay. By introducing mode-dependent double event-triggering mechanisms (DETMs), the communication resources in both system-controller (S-C) channe...
Neural Networks, Computer Algorithms Computer Simulation Communication Time Factors
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Evolving and Incremental Value Iteration Schemes for Nonlinear Discrete-Time Zero-Sum Games.

IEEE transactions on cybernetics Jun 15, 2023
In this article, evolving and incremental value iteration (VI) frameworks are constructed to address the discrete-time zero-sum game problem. First, the evolving scheme means that the closed-loop system is regulated by using the evolving policy pair....
Computer Simulation Nonlinear Dynamics Neural Networks, Computer Algorithms
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Design computed torque control for Stewart platform with uncertainty to the rehabilitation of patients with leg disabilities.

Computer methods in biomechanics and biomedical engineering Jun 14, 2023
Physiotherapy is a treatment that may be required permanently by many patients. As a result, a robot that can execute physiotherapy exercises for the legs like a professional therapist with adequate performance and acceptable safety may be efficient ...
Persons with Disabilities Robotics Humans Computer Simulation Leg Uncertainty Equipment Design Torque
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A novel collaborative self-supervised learning method for radiomic data.

NeuroImage Jun 14, 2023
The computer-aided disease diagnosis from radiomic data is important in many medical applications. However, developing such a technique relies on labeling radiological images, which is a time-consuming, labor-intensive, and expensive process. In this...
Humans Computer Simulation Diagnosis, Computer-Assisted Supervised Machine Learning
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Prediction of Human Organ Toxicity via Artificial Intelligence Methods.

Chemical research in toxicology Jun 10, 2023
Unpredicted human organ level toxicity remains one of the major reasons for drug clinical failure. There is a critical need for cost-efficient strategies in the early stages of drug development for human toxicity assessment. At present, artificial in...
Artificial Intelligence Algorithms Humans Computer Simulation Machine Learning Drug Discovery
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