AIMC Topic: Neural Networks, Computer

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Synthetic CT image generation of shape-controlled lung cancer using semi-conditional InfoGAN and its applicability for type classification.

International journal of computer assisted radiology and surgery
PURPOSE: In recent years, convolutional neural network (CNN), an artificial intelligence technology with superior image recognition, has become increasingly popular and frequently used for classification tasks in medical imaging. However, the amount ...

Shallow Graph Convolutional Network for Skeleton-Based Action Recognition.

Sensors (Basel, Switzerland)
Graph convolutional networks (GCNs) have brought considerable improvement to the skeleton-based action recognition task. Existing GCN-based methods usually use the fixed spatial graph size among all the layers. It severely affects the model's abiliti...

Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning.

Sensors (Basel, Switzerland)
This paper explores how well deep learning models trained on chest CT images can diagnose COVID-19 infected people in a fast and automated process. To this end, we adopted advanced deep network architectures and proposed a transfer learning strategy ...

Transformer neural network for protein-specific de novo drug generation as a machine translation problem.

Scientific reports
Drug discovery for a protein target is a very laborious, long and costly process. Machine learning approaches and, in particular, deep generative networks can substantially reduce development time and costs. However, the majority of methods imply pri...

Anti-senescent drug screening by deep learning-based morphology senescence scoring.

Nature communications
Advances in deep learning technology have enabled complex task solutions. The accuracy of image classification tasks has improved owing to the establishment of convolutional neural networks (CNN). Cellular senescence is a hallmark of ageing and is im...

Screening of sleep apnea based on heart rate variability and long short-term memory.

Sleep & breathing = Schlaf & Atmung
PURPOSE: Sleep apnea syndrome (SAS) is a prevalent sleep disorder in which apnea and hypopnea occur frequently during sleep and result in increase of the risk of lifestyle-related disease development as well as daytime sleepiness. Although SAS is a c...

HIVE-Net: Centerline-aware hierarchical view-ensemble convolutional network for mitochondria segmentation in EM images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: With the advancement of electron microscopy (EM) imaging technology, neuroscientists can investigate the function of various intracellular organelles, e.g, mitochondria, at nano-scale. Semantic segmentation of electron micro...

A comprehensive comparison of molecular feature representations for use in predictive modeling.

Computers in biology and medicine
Machine learning methods are commonly used for predicting molecular properties to accelerate material and drug design. An important part of this process is deciding how to represent the molecules. Typically, machine learning methods expect examples r...

Chest X-ray image phase features for improved diagnosis of COVID-19 using convolutional neural network.

International journal of computer assisted radiology and surgery
PURPOSE: Recently, the outbreak of the novel coronavirus disease 2019 (COVID-19) pandemic has seriously endangered human health and life. In fighting against COVID-19, effective diagnosis of infected patient is critical for preventing the spread of d...

An artificial neural network based mathematical model for a stochastic health care facility location problem.

Health care management science
This research is conducted to investigate the problem of locating the trauma centers and helicopters' station in order to optimize the trauma care system. The stochastic characteristics of the system, such as stochastic transferring time of the patie...