AIMC Topic: Neural Networks, Computer

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The importance of recurrent top-down synaptic connections for the anticipation of dynamic emotions.

Neural networks : the official journal of the International Neural Network Society
Different studies have shown the efficiency of a feed-forward neural network in categorizing basic emotional facial expressions. However, recent findings in psychology and cognitive neuroscience suggest that visual recognition is not a pure bottom-up...

Detection of Traumatic Pediatric Elbow Joint Effusion Using a Deep Convolutional Neural Network.

AJR. American journal of roentgenology
OBJECTIVE: The purpose of this study is to determine whether a deep convolutional neural network (DCNN) trained on a dataset of limited size can accurately diagnose traumatic pediatric elbow effusion on lateral radiographs.

TopScore: Using Deep Neural Networks and Large Diverse Data Sets for Accurate Protein Model Quality Assessment.

Journal of chemical theory and computation
The value of protein models obtained with automated protein structure prediction depends primarily on their accuracy. Protein model quality assessment is thus critical to select the model that can best answer biologically relevant questions from an e...

Estimating Missing Data in Temporal Data Streams Using Multi-Directional Recurrent Neural Networks.

IEEE transactions on bio-medical engineering
Missing data is a ubiquitous problem. It is especially challenging in medical settings because many streams of measurements are collected at different-and often irregular-times. Accurate estimation of the missing measurements is critical for many rea...

ScatterNet: A convolutional neural network for cone-beam CT intensity correction.

Medical physics
PURPOSE: To demonstrate a proof-of-concept for fast cone-beam CT (CBCT) intensity correction in projection space by the use of deep learning.

Medical Image Analysis using Convolutional Neural Networks: A Review.

Journal of medical systems
The science of solving clinical problems by analyzing images generated in clinical practice is known as medical image analysis. The aim is to extract information in an affective and efficient manner for improved clinical diagnosis. The recent advance...

Interactive reservoir computing for chunking information streams.

PLoS computational biology
Chunking is the process by which frequently repeated segments of temporal inputs are concatenated into single units that are easy to process. Such a process is fundamental to time-series analysis in biological and artificial information processing sy...

Social Touch Gesture Recognition Using Convolutional Neural Network.

Computational intelligence and neuroscience
Recently, social touch gesture recognition has been considered an important topic for touch modality, which can lead to highly efficient and realistic human-robot interaction. In this paper, a deep convolutional neural network is selected to implemen...

Decision-Tree Based Meta-Strategy Improved Accuracy of Disorder Prediction and Identified Novel Disordered Residues Inside Binding Motifs.

International journal of molecular sciences
Using computational techniques to identify intrinsically disordered residues is practical and effective in biological studies. Therefore, designing novel high-accuracy strategies is always preferable when existing strategies have a lot of room for im...

Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks.

NeuroImage
The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and long...