Infectious Disease

Audits and COVID-19: A paradigm shift in the making.

The COVID-19 pandemic has exposed the obsolescence and vulnerability of many existing auditing practices. While some progressive practices have been implemented (e.g., remote audits using rudimentary information and communication technologies), a new paradigm is needed not only to account for the risk of repeated lockdowns but also to align practices with the level of digitalization, automation, a...

A Bio-inspired trajectory planning method for robotic manipulators based on improved bacteria foraging optimization algorithm and tau theory.

In this paper, a novel bio-inspired trajectory planning method is proposed for robotic systems based on an improved bacteria foraging optimization algorithm (IBFOA) and an improved intrinsic Tau jerk (named Tau-J*) guidance strategy. Besides, the adaptive factor and elite-preservation strategy are employed to facilitate the IBFOA, and an improved Tau-J* with higher-order of intrinsic guidance move...

Artificial intelligence for imaging-based COVID-19 detection: Systematic review comparing added value of AI versus human readers.

PURPOSE: A growing number of studies have examined whether Artificial Intelligence (AI) systems can support imaging-based diagnosis of COVID-19-caused...

Assessing a fossil fuels externality with a new neural networks and image optimisation algorithm: the case of atmospheric pollutants as confounders to COVID-19 lethality.

This paper demonstrates how the combustion of fossil fuels for transport purpose might cause health implications. Based on an original case study [i.e...

A baseline model including quantitative anti-HBc to predict response of peginterferon in HBeAg-positive chronic hepatitis B patients.

BACKGROUND: Few models to predict antiviral response of peginterferon were used in hepatitis B e antigen (HBeAg)-positive chronic hepatitis B patients...

Potential diagnosis of COVID-19 from chest X-ray and CT findings using semi-supervised learning.

COVID-19 is an infectious disease, which has adversely affected public health and the economy across the world. On account of the highly infectious na...

An Optimized Hybrid Deep Learning Model to Detect COVID-19 Misleading Information.

Fake news is challenging to detect due to mixing accurate and inaccurate information from reliable and unreliable sources. Social media is a data sour...

Detection of Fake News Text Classification on COVID-19 Using Deep Learning Approaches.

A vast amount of data is generated every second for microblogs, content sharing via social media sites, and social networking. Twitter is an essential...

Perplexing issues for convalescent immune plasma therapy in COVID-19.

Convalescent immune plasma (CIP) therapy in coronavirus disease 2019 (COVID-19) is presently a trendy choice of treatment. On March 24, 2020, the Unit...

Factors That Influence Risk Perceptions and Successful COVID-19 Vaccination Communication Campaigns With American Indians.

COVID-19 vaccinations are the primary tool to end the pandemic. However, vaccine hesitancy continues to be a barrier to herd-immunity in the United St...

Is skipping the definition of primary and secondary models possible? Prediction of Escherichia coli O157 growth by machine learning.

To predict bacterial population behavior in food, statistical models with specific function form have been applied in the field of predictive microbio...

Leveraging machine learning essentiality predictions and chemogenomic interactions to identify antifungal targets.

Fungal pathogens pose a global threat to human health, with Candida albicans among the leading killers. Systematic analysis of essential genes provide...

A Fluorescent Biosensor for Sensitive Detection of Typhimurium Using Low-Gradient Magnetic Field and Deep Learning via Faster Region-Based Convolutional Neural Network.

In this study, a fluorescent biosensor was developed for the sensitive detection of typhimurium using a low-gradient magnetic field and deep learning...

COVID-19 cough sound symptoms classification from scalogram image representation using deep learning models.

Deep Learning shows promising performance in diverse fields and has become an emerging technology in Artificial Intelligence. Recent visual recognitio...

An accurate artificial intelligence system for the detection of pulmonary and extra pulmonary Tuberculosis.

Tuberculosis (TB) is the greatest irresistible illness in humans, caused by microbes Mycobacterium TB (MTB) bacteria and is an infectious disease that...

Prediction of antimicrobial peptides toxicity based on their physico-chemical properties using machine learning techniques.

BACKGROUND: Antimicrobial peptides are promising tools to fight against ever-growing antibiotic resistance. However, despite many advantages, their to...

A Machine Learning-Based Screening Test for Sarcopenic Dysphagia Using Image Recognition.

BACKGROUND: Sarcopenic dysphagia, a swallowing disorder caused by sarcopenia, is prevalent in older patients and can cause malnutrition and aspiration...

Computational methods directed towards drug repurposing for COVID-19: advantages and limitations.

Novel coronavirus disease 2019 (COVID-19) has significantly altered the socio-economic status of countries. Although vaccines are now available agains...

Bacterial coinfections with coronavirus disease 2019 (COVID-19).

BACKGROUND: The pandemic caused by severe acute respiratory coronavirus virus 2 (SARS-CoV-2) has dramatically increased cheshospitalizations, and it i...

[Development of severity and mortality prediction models for covid-19 patients at emergency department including the chest x-ray].

OBJECTIVES: To develop prognosis prediction models for COVID-19 patients attending an emergency department (ED) based on initial chest X-ray (CXR), de...