AIMC Topic: COVID-19

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Hierarchical graph-based integration network for propaganda detection in textual news articles on social media.

Scientific reports
During the Covid-19 pandemic, the widespread use of social media platforms has facilitated the dissemination of information, fake news, and propaganda, serving as a vital source of self-reported symptoms related to Covid-19. Existing graph-based mode...

AI based medical imagery diagnosis for COVID-19 disease examination and remedy.

Scientific reports
COVID-19, caused by the SARS-CoV-2 coronavirus, has spread to more than 200 countries, affecting millions, costing billions, and claiming nearly 2 million lives since late 2019. This highly contagious disease can easily overwhelm healthcare systems i...

TBE-Net: A Deep Network Based on Tree-Like Branch Encoder for Medical Image Segmentation.

IEEE journal of biomedical and health informatics
In recent years, encoder-decoder-based network structures have been widely used in designing medical image segmentation models. However, these methods still face some limitations: 1) The network's feature extraction capability is limited, primarily d...

Acoustic COVID-19 Detection Using Multiple Instance Learning.

IEEE journal of biomedical and health informatics
In the COVID-19 pandemic, a rigorous testing scheme was crucial. However, tests can be time-consuming and expensive. A machine learning-based diagnostic tool for audio recordings could enable widespread testing at low costs. In order to achieve compa...

High performance COVID-19 screening using machine learning.

La Tunisie medicale
Since the World Health Organization declared the Coronavirus Disease 2019 (COVID-19) pandemic as an international concern of public health emergency in the early 2020, several strategies have been initiated in many countries to prevent healthcare ser...

Managing emergency crises using secure information through educational awareness: COVID-19 case study.

Computers in biology and medicine
Social networks are increasingly taking over daily life, creating a volume of unsecured data and making it very difficult to capture safe data, especially in times of crisis. This study aims to use a Convolutional Neural Network (CNN)-Long Short-Term...

Psychotropic medications: a descriptive study of prescription trends in Tabriz, Iran, 2021-2022.

BMC psychiatry
INTRODUCTION: Mental disorders, such as anxiety and depression, significantly impacted global populations in 2019 and 2020, with COVID-19 causing a surge in prevalence. They affect 13.4% of the people worldwide, and 21% of Iranians have experienced t...

The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development.

Molecular biomedicine
Integrating Artificial Intelligence (AI) across numerous disciplines has transformed the worldwide landscape of pandemic response. This review investigates the multidimensional role of AI in the pandemic, which arises as a global health crisis, and i...

Stress Monitoring in Pandemic Screening: Insights from GSR Sensor and Machine Learning Analysis.

Biosensors
This study investigates the impact of patient stress on COVID-19 screening. An attempt was made to measure the level of anxiety of individuals undertaking rapid tests for SARS-CoV-2. To this end, a galvanic skin response (GSR) sensor that was connect...

Exploring happiness factors with explainable ensemble learning in a global pandemic.

PloS one
Happiness is a state of contentment, joy, and fulfillment, arising from relationships, accomplishments, and inner peace, leading to well-being and positivity. The greatest happiness principle posits that morality is determined by pleasure, aiming for...