AIMC Topic: Numerical Analysis, Computer-Assisted
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Fast and accurate modeling of transient-state, gradient-spoiled sequences by recurrent neural networks.
NMR in biomedicine
May 5, 2021
Fast and accurate modeling of MR signal responses are typically required for various quantitative MRI applications, such as MR fingerprinting. This work uses a new extended phase graph (EPG)-Bloch model for accurate simulation of transient-state, gra...
Numerical simulation of deformed red blood cell by utilizing neural network approach and finite element analysis.
Computer methods in biomechanics and biomedical engineering
Aug 10, 2020
In order to have research on the deformation characteristics and mechanical properties of human red blood cells (RBCs), finite element models of RBC optical tweezers stretching and atomic force microscope (AFM) indentation were established. Non-linea...
Deep complex convolutional network for fast reconstruction of 3D late gadolinium enhancement cardiac MRI.
NMR in biomedicine
Apr 30, 2020
Several deep-learning models have been proposed to shorten MRI scan time. Prior deep-learning models that utilize real-valued kernels have limited capability to learn rich representations of complex MRI data. In this work, we utilize a complex-valued...
Numerosity discrimination in deep neural networks: Initial competence, developmental refinement and experience statistics.
Developmental science
Feb 18, 2020
Both humans and non-human animals exhibit sensitivity to the approximate number of items in a visual array, as indexed by their performance in numerosity discrimination tasks, and even neonates can detect changes in numerosity. These findings are oft...
Craniobot: A computer numerical controlled robot for cranial microsurgeries.
Scientific reports
Jan 31, 2019
Over the last few decades, a plethora of tools has been developed for neuroscientists to interface with the brain. Implementing these tools requires precisely removing sections of the skull to access the brain. These delicate cranial microsurgical pr...
Gaussian process classification of superparamagnetic relaxometry data: Phantom study.
Artificial intelligence in medicine
Jul 24, 2017
MOTIVATION: Superparamagnetic relaxometry (SPMR) is an emerging technology that holds potential for use in early cancer detection. Measurement of the magnetic field after the excitation of cancer-bound superparamagnetic iron oxide nanoparticles (SPIO...
Image Processing, Computer-Assisted
Mice
Contrast Media
Predictive Value of Tests
Magnetite Nanoparticles
Magnetic Resonance Imaging
Early Detection of Cancer
Algorithms
Computer Simulation
Reproducibility of Results
Animals
Machine Learning
Phantoms, Imaging
Normal Distribution
Signal-To-Noise Ratio
Numerical Analysis, Computer-Assisted
Magnetics
Neoplasms, Experimental
A machine learning approach to investigate the relationship between shape features and numerically predicted risk of ascending aortic aneurysm.
Biomechanics and modeling in mechanobiology
Apr 6, 2017
Geometric features of the aorta are linked to patient risk of rupture in the clinical decision to electively repair an ascending aortic aneurysm (AsAA). Previous approaches have focused on relationship between intuitive geometric features (e.g., diam...
Generating highly accurate prediction hypotheses through collaborative ensemble learning.
Scientific reports
Mar 17, 2017
Ensemble generation is a natural and convenient way of achieving better generalization performance of learning algorithms by gathering their predictive capabilities. Here, we nurture the idea of ensemble-based learning by combining bagging and boosti...
gDNA-Prot: Predict DNA-binding proteins by employing support vector machine and a novel numerical characterization of protein sequence.
Journal of theoretical biology
Jul 1, 2016
DNA-binding proteins are the functional proteins in cells, which play an important role in various essential biological activities. An effective and fast computational method gDNA-Prot is proposed to predict DNA-binding proteins in this paper, which ...
The tool for the automatic analysis of lexical sophistication (TAALES): version 2.0.
Behavior research methods
Jun 1, 2018
This study introduces the second release of the Tool for the Automatic Analysis of Lexical Sophistication (TAALES 2.0), a freely available and easy-to-use text analysis tool. TAALES 2.0 is housed on a user's hard drive (allowing for secure data proce...
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