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Pandemics

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On the Use of Deep Learning for Imaging-Based COVID-19 Detection Using Chest X-rays.

Sensors (Basel, Switzerland)
The global COVID-19 pandemic that started in 2019 and created major disruptions around the world demonstrated the imperative need for quick, inexpensive, accessible and reliable diagnostic methods that would allow the detection of infected individual...

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...

Natural Language Processing Insight into LGBTQ+ Youth Mental Health During the COVID-19 Pandemic: Longitudinal Content Analysis of Anxiety-Provoking Topics and Trends in Emotion in LGBTeens Microcommunity Subreddit.

JMIR public health and surveillance
BACKGROUND: Widespread fear surrounding COVID-19, coupled with physical and social distancing orders, has caused severe adverse mental health outcomes. Little is known, however, about how the COVID-19 crisis has impacted LGBTQ+ youth, who disproporti...

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...

LUNAR :Drug Screening for Novel Coronavirus Based on Representation Learning Graph Convolutional Network.

IEEE/ACM transactions on computational biology and bioinformatics
An outbreak of COVID-19 that began in late 2019 was caused by a novel coronavirus(SARS-CoV-2). It has become a global pandemic. As of June 9, 2020, it has infected nearly 7 million people and killed more than 400,000, but there is no specific drug. T...

Deep Bidirectional Classification Model for COVID-19 Disease Infected Patients.

IEEE/ACM transactions on computational biology and bioinformatics
In December of 2019, a novel coronavirus (COVID-19) appeared in Wuhan city, China and has been reported in many countries with millions of people infected within only four months. Chest computed Tomography (CT) has proven to be a useful supplement to...

Machine learning based approach to exam cheating detection.

PloS one
The COVID-19 pandemic has impelled the majority of schools and universities around the world to switch to remote teaching. One of the greatest challenges in online education is preserving the academic integrity of student assessments. The lack of dir...

The Humanoid Robot Sil-Bot in a Cognitive Training Program for Community-Dwelling Elderly People with Mild Cognitive Impairment during the COVID-19 Pandemic: A Randomized Controlled Trial.

International journal of environmental research and public health
BACKGROUND: Mild cognitive impairment (MCI) is a stage preceding dementia, and early intervention is critical. This study investigated whether multi-domain cognitive training programs, especially robot-assisted training, conducted 12 times, twice a w...

Hybrid Deep-Learning and Machine-Learning Models for Predicting COVID-19.

Computational intelligence and neuroscience
The COVID-19 pandemic has had a significant impact on public life and health worldwide, putting the world's healthcare systems at risk. The first step in stopping this outbreak is to detect the infection in its early stages, which will relieve the ri...