AIMC Topic: Neural Networks, Computer

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Leveraging graph neural networks for supporting automatic triage of patients.

Scientific reports
Patient triage is crucial in emergency departments, ensuring timely and appropriate care based on correctly evaluating the emergency grade of patient conditions. Triage methods are generally performed by human operator based on her own experience and...

Investigation on ultrasound images for detection of fetal congenital heart defects.

Biomedical physics & engineering express
Congenital heart defects (CHD) are one of the serious problems that arise during pregnancy. Early CHD detection reduces death rates and morbidity but is hampered by the relatively low detection rates (i.e., 60%) of current screening technology. The d...

How well do models of visual cortex generalize to out of distribution samples?

PLoS computational biology
Unit activity in particular deep neural networks (DNNs) are remarkably similar to the neuronal population responses to static images along the primate ventral visual cortex. Linear combinations of DNN unit activities are widely used to build predicti...

Estimating receptive fields of simple and complex cells in early visual cortex: A convolutional neural network model with parameterized rectification.

PLoS computational biology
Neurons in the primary visual cortex respond selectively to simple features of visual stimuli, such as orientation and spatial frequency. Simple cells, which have phase-sensitive responses, can be modeled by a single receptive field filter in a linea...

: a novel hybrid quasi-fuzzy artificial neural network (ANN) model for estimation of reference evapotranspiration.

PeerJ
Reference evapotranspiration ( ) is a significant parameter for efficient irrigation scheduling and groundwater conservation. Different machine learning models have been designed for estimation for specific combinations of available meteorological p...

Improved U-net network asphalt pavement crack detection method.

PloS one
Road crack detection is one of the important parts of road safety detection. Aiming at the problems such as weak segmentation effect of basic U-Net on pavement crack, insufficient precision of crack contour segmentation, difficult to identify narrow ...

DAU-Net: Dual attention-aided U-Net for segmenting tumor in breast ultrasound images.

PloS one
Breast cancer remains a critical global concern, underscoring the urgent need for early detection and accurate diagnosis to improve survival rates among women. Recent developments in deep learning have shown promising potential for computer-aided det...

A Hybrid convolution neural network for the classification of tree species using hyperspectral imagery.

PloS one
In recent years, the advancement of hyperspectral remote sensing technology has greatly enhanced the detailed mapping of tree species. Nevertheless, delving deep into the significance of hyperspectral remote sensing data features for tree species rec...

Visual explanations for polyp detection: How medical doctors assess intrinsic versus extrinsic explanations.

PloS one
Deep learning has achieved immense success in computer vision and has the potential to help physicians analyze visual content for disease and other abnormalities. However, the current state of deep learning is very much a black box, making medical pr...

Classifying Routine Clinical Electroencephalograms With Multivariate Iterative Filtering and Convolutional Neural Networks.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Electroencephalogram (EEG) is widely used in basic and clinical neuroscience to explore neural states in various populations, and classifying these EEG recordings is a fundamental challenge. While machine learning shows promising results in classifyi...