AIMC Topic: Neural Networks, Computer

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A Morphologically Individualized Deep Learning Brain Injury Model.

Journal of neurotrauma
The brain injury modeling community has recommended improving model subject specificity and simulation efficiency. Here, we extend an instantaneous (< 1 sec) convolutional neural network (CNN) brain model based on the anisotropic Worcester Head Injur...

Approximation of smooth functionals using deep ReLU networks.

Neural networks : the official journal of the International Neural Network Society
In recent years, deep neural networks have been employed to approximate nonlinear continuous functionals F defined on L([-1,1]) for 1≤p≤∞. However, the existing theoretical analysis in the literature either is unsatisfactory due to the poor approxima...

Predicting new drug indications based on double variational autoencoders.

Computers in biology and medicine
Experimental drug development is costly, complex, and time-consuming, and the number of drugs that have been put into application treatment is small. The identification of drug-disease correlations can provide important information for drug discovery...

Patient Clustering for Vital Organ Failure Using ICD Code With Graph Attention.

IEEE transactions on bio-medical engineering
OBJECTIVE: Heart failure, respiratory failure and kidney failure are three severe organ failures (OF) that have high mortalities and are most prevalent in intensive care units. The objective of this work is to offer insights into OF clustering from t...

A Feature Space-Restricted Attention Attack on Medical Deep Learning Systems.

IEEE transactions on cybernetics
Deep neural network has shown a powerful performance in the medical image analysis of a variety of diseases. However, a number of studies over the past few years have demonstrated that these deep learning systems can be vulnerable to well-designed ad...

Human Activity Prediction Based on Forecasted IMU Activity Signals by Sequence-to-Sequence Deep Neural Networks.

Sensors (Basel, Switzerland)
Human Activity Recognition (HAR) has gained significant attention due to its broad range of applications, such as healthcare, industrial work safety, activity assistance, and driver monitoring. Most prior HAR systems are based on recorded sensor data...

P-TransUNet: an improved parallel network for medical image segmentation.

BMC bioinformatics
Deep learning-based medical image segmentation has made great progress over the past decades. Scholars have proposed many novel transformer-based segmentation networks to solve the problems of building long-range dependencies and global context conne...

CellSighter: a neural network to classify cells in highly multiplexed images.

Nature communications
Multiplexed imaging enables measurement of multiple proteins in situ, offering an unprecedented opportunity to chart various cell types and states in tissues. However, cell classification, the task of identifying the type of individual cells, remains...

An artificial intelligence approach for identification of microalgae cultures.

New biotechnology
In this work, a model for the characterization of microalgae cultures based on artificial neural networks has been developed. The characterization of microalgae cultures is essential to guarantee the quality of the biomass, and the objective of this ...