AIMC Topic: Pandemics

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Fog-based deep learning framework for real-time pandemic screening in smart cities from multi-site tomographies.

BMC medical imaging
The quick proliferation of pandemic diseases has been imposing many concerns on the international health infrastructure. To combat pandemic diseases in smart cities, Artificial Intelligence of Things (AIoT) technology, based on the integration of art...

COVID‑19 detection from chest X-ray images using transfer learning.

Scientific reports
COVID-19 is a kind of coronavirus that appeared in China in the Province of Wuhan in December 2019. The most significant influence of this virus is its very highly contagious characteristic which may lead to death. The standard diagnosis of COVID-19 ...

A complex fuzzy decision model for analysing the post-pandemic immuno-sustainability.

Acta tropica
The post-effects of the COronaVIrus Disease (COVID-19) vary depending on socioeconomic and biological factors. Similarly, the effects of vaccination on people's immunity vary across several factors. After the pandemic, real-life post-vaccination anom...

Random forest models of food safety behavior during the COVID-19 pandemic.

International journal of environmental health research
Machine learning approaches are increasingly being adopted as data analysis tools in scientific behavioral predictions. This paper utilizes a machine learning approach, Random Forest Model, to determine the top prediction variables of food safety beh...

Workout Classification Using a Convolutional Neural Network in Ensemble Learning.

Sensors (Basel, Switzerland)
To meet the increased demand for home workouts owing to the COVID-19 pandemic, this study proposes a new approach to real-time exercise posture classification based on the convolutional neural network (CNN) in an ensemble learning system. By utilizin...

A Retrospective Analysis of Indoor CO Measurements Obtained with a Mobile Robot during the COVID-19 Pandemic.

Sensors (Basel, Switzerland)
This work presents a retrospective analysis of indoor CO measurements obtained with a mobile robot in an educational building after the COVID-19 lockdown (May 2021), at a time when public activities resumed with mandatory local pandemic restrictions....

Predicting the Utility of Scientific Articles for Emerging Pandemics Using Their Titles and Natural Language Processing.

Disaster medicine and public health preparedness
OBJECTIVE: Not all scientific publications are equally useful to policy-makers tasked with mitigating the spread and impact of diseases, especially at the start of novel epidemics and pandemics. The urgent need for actionable, evidence-based informat...

Key determinants to supply chain resilience to face pandemic disruption: An interpretive triple helix framework.

PloS one
Today, supply chain (SC) networks are facing more disruptions compared to the past. While disruptions are rare, they can have catastrophic long-term economic or societal repercussions, and the recovery processes can be lengthy. These can tremendously...

Impact of COVID-19 Pandemic on Social Determinants of Health Issues of Marginalized Black and Asian Communities: A Social Media Analysis Empowered by Natural Language Processing.

Journal of racial and ethnic health disparities
PURPOSE: This study aims to understand the impact of the COVID-19 pandemic on social determinants of health (SDOH) of marginalized racial/ethnic US population groups, specifically African Americans and Asians, by leveraging natural language processin...

ISMI-VAE: A deep learning model for classifying disease cells using gene expression and SNV data.

Computers in biology and medicine
Various studies have linked several diseases, including cancer and COVID-19, to single nucleotide variations (SNV). Although single-cell RNA sequencing (scRNA-seq) technology can provide SNV and gene expression data, few studies have integrated and a...