AIMC Topic: Neural Networks, Computer

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How network structure affects the dynamics of a network of stochastic spiking neurons.

Chaos (Woodbury, N.Y.)
Up to now, it still remains an open question about the relation between the structure of brain networks and their functions. The effects of structure on the dynamics of neural networks are usually investigated via extensive numerical simulations, whi...

ComBat Harmonization for MRI Radiomics: Impact on Nonbinary Tissue Classification by Machine Learning.

Investigative radiology
OBJECTIVES: The aims of this study were to determine whether ComBat harmonization improves multiclass radiomics-based tissue classification in technically heterogeneous MRI data sets and to compare the performances of 2 ComBat variants.

A convolutional neural network-based decision support system for neonatal quiet sleep detection.

Mathematical biosciences and engineering : MBE
Sleep plays an important role in neonatal brain and physical development, making its detection and characterization important for assessing early-stage development. In this study, we propose an automatic and computationally efficient algorithm to det...

Neural potentials of proteins extrapolate beyond training data.

The Journal of chemical physics
We evaluate neural network (NN) coarse-grained (CG) force fields compared to traditional CG molecular mechanics force fields. We conclude that NN force fields are able to extrapolate and sample from unseen regions of the free energy surface when trai...

Narrowing the gap: expected versus deployment performance.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Successful model development requires both an accurate a priori understanding of future performance and high performance on deployment. Optimistic estimations of model performance that are unrealized in real-world clinical settings can co...

Tuning Criticality through Modularity in Biological Neural Networks.

The Journal of neuroscience : the official journal of the Society for Neuroscience

SEINN: A deep learning algorithm for the stochastic epidemic model.

Mathematical biosciences and engineering : MBE
Stochastic modeling predicts various outcomes from stochasticity in the data, parameters and dynamical system. Stochastic models are deemed more appropriate than deterministic models accounting in terms of essential and practical information about a ...

Developing a Deep Neural Network model for COVID-19 diagnosis based on CT scan images.

Mathematical biosciences and engineering : MBE
COVID-19 is most commonly diagnosed using a testing kit but chest X-rays and computed tomography (CT) scan images have a potential role in COVID-19 diagnosis. Currently, CT diagnosis systems based on Artificial intelligence (AI) models have been used...