AIMC Topic: SARS-CoV-2

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Optimal Diagnosis of COVID-19 Based on Convolutional Neural Network and Red Fox Optimization Algorithm.

Computational intelligence and neuroscience
SARS-CoV-2 is a specific type of Coronavirus that was firstly reported in China in December 2019 and is the causative agent of coronavirus disease 2019 (COVID-19). In March 2020, this disease spread to different parts of the world causing a global pa...

COVID-19 sentiment analysis via deep learning during the rise of novel cases.

PloS one
Social scientists and psychologists take interest in understanding how people express emotions and sentiments when dealing with catastrophic events such as natural disasters, political unrest, and terrorism. The COVID-19 pandemic is a catastrophic ev...

Development and Progress in Sensors and Technologies for Human Emotion Recognition.

Sensors (Basel, Switzerland)
With the advancement of human-computer interaction, robotics, and especially humanoid robots, there is an increasing trend for human-to-human communications over online platforms (e.g., zoom). This has become more significant in recent years due to t...

Robotics for neuroendovascular intervention: Background and primer.

The neuroradiology journal
The simultaneous growth of robotic-assisted surgery and telemedicine in recent years has only been accelerated by the recent coronavirus disease 2019 pandemic. Robotic assistance for neurovascular intervention has garnered significant interest due to...

SCAPTURE: a deep learning-embedded pipeline that captures polyadenylation information from 3' tag-based RNA-seq of single cells.

Genome biology
Single-cell RNA-seq (scRNA-seq) profiles gene expression with high resolution. Here, we develop a stepwise computational method-called SCAPTURE to identify, evaluate, and quantify cleavage and polyadenylation sites (PASs) from 3' tag-based scRNA-seq....

Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection.

Scientific reports
To speed up the discovery of COVID-19 disease mechanisms by X-ray images, this research developed a new diagnosis platform using a deep convolutional neural network (DCNN) that is able to assist radiologists with diagnosis by distinguishing COVID-19 ...

Validating deep learning inference during chest X-ray classification for COVID-19 screening.

Scientific reports
The new coronavirus unleashed a worldwide pandemic in early 2020, and a fatality rate several times that of the flu. As the number of infections soared, and capabilities for testing lagged behind, chest X-ray (CXR) imaging became more relevant in the...

Toward a systematic conflict resolution framework for ontologies.

Journal of biomedical semantics
BACKGROUND: The ontology authoring step in ontology development involves having to make choices about what subject domain knowledge to include. This may concern sorting out ontological differences and making choices between conflicting axioms due to ...

Deep learning and lung ultrasound for Covid-19 pneumonia detection and severity classification.

Computers in biology and medicine
The Covid-19 European outbreak in February 2020 has challenged the world's health systems, eliciting an urgent need for effective and highly reliable diagnostic instruments to help medical personnel. Deep learning (DL) has been demonstrated to be use...

An approach to the classification of COVID-19 based on CT scans using convolutional features and genetic algorithms.

Computers in biology and medicine
COVID-19 is a respiratory disease that, as of July 15th, 2021, has infected more than 187 million people worldwide and is responsible for more than 4 million deaths. An accurate diagnosis of COVID-19 is essential for the treatment and control of the ...