AIMC Topic: Neural Networks, Computer

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Spatial coordinate transforms linking the allocentric hippocampal and egocentric parietal primate brain systems for memory, action in space, and navigation.

Hippocampus
A theory and model of spatial coordinate transforms in the dorsal visual system through the parietal cortex that enable an interface via posterior cingulate and related retrosplenial cortex to allocentric spatial representations in the primate hippoc...

Multi-resolution convolutional neural networks for fully automated segmentation of acutely injured lungs in multiple species.

Medical image analysis
Segmentation of lungs with acute respiratory distress syndrome (ARDS) is a challenging task due to diffuse opacification in dependent regions which results in little to no contrast at the lung boundary. For segmentation of severely injured lungs, loc...

ARPNet: Antidepressant Response Prediction Network for Major Depressive Disorder.

Genes
Treating patients with major depressive disorder is challenging because it takes several months for antidepressants prescribed for the patients to take effect. This limitation may result in increased risks and treatment costs. To address this limitat...

An artificial neural network ensemble approach to generate air pollution maps.

Environmental monitoring and assessment
The objective of this research is to propose an artificial neural network (ANN) ensemble in order to estimate the hourly NO concentration at unsampled locations. Spatial interpolation methods and linear regression models with regularization have been...

ThalPred: a web-based prediction tool for discriminating thalassemia trait and iron deficiency anemia.

BMC medical informatics and decision making
BACKGROUND: The hypochromic microcytic anemia (HMA) commonly found in Thailand are iron deficiency anemia (IDA) and thalassemia trait (TT). Accurate discrimination between IDA and TT is an important issue and better methods are urgently needed. Altho...

Can Signal Delay be Functional? Including Delay in Evolved Robot Controllers.

Artificial life
Engineers, control theorists, and neuroscientists often view the delay imposed by finite signal propagation velocities as a problem that needs to be compensated for or avoided. In this article, we consider the alternative possibility that in some cas...

Classification of DNA damages on segmented comet assay images using convolutional neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Identification and quantification of DNA damage is a very significant subject in biomedical research area which still needs more robust and effective methods. One of the cheapest, easy to use and most successful method for D...

Feasibility of two-dimensional dose distribution deconvolution using convolution neural networks.

Medical physics
PURPOSE: The purpose of this study was to investigate the feasibility of two-dimensional (2D) dose distribution deconvolution using convolutional neural networks (CNNs) instead of an analytical approach for an in-house scintillation detector that has...

Automatic classification of lung nodule candidates based on a novel 3D convolution network and knowledge transferred from a 2D network.

Medical physics
OBJECTIVE: In the automatic lung nodule detection system, the authenticity of a large number of nodule candidates needs to be judged, which is a classification task. However, the variable shapes and sizes of the lung nodules have posed a great challe...