Pneumonia

A computer-aided diagnosis system for the classification of COVID-19 and non-COVID-19 pneumonia on chest X-ray images by integrating CNN with sparse autoencoder and feed forward neural network.

Several infectious diseases have affected the lives of many people and have caused great dilemmas all over the world. COVID-19 was declared a pandemic caused by a newly discovered virus named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) by the World Health Organisation in 2019. RT-PCR is considered the golden standard for COVID-19 detection. Due to the limited RT-PCR resources, ear...

Lung detection and severity prediction of pneumonia patients based on COVID-19 DET-PRE network.

BACKGROUND: The sudden outbreak of COVID-19 pneumonia has brought a heavy disaster to individuals globally. Facing this new virus, the clinicians have no automatic tools to assess the severity of pneumonia patients.

Twitter sentiment analysis from Iran about COVID 19 vaccine.

BACKGROUND AND AIMS: The development of vaccines against COVID-19 has been a global purpose since the World Health Organization declared the pandemic....

Independent evaluation of 12 artificial intelligence solutions for the detection of tuberculosis.

There have been few independent evaluations of computer-aided detection (CAD) software for tuberculosis (TB) screening, despite the rapidly expanding ...

Optimization: Molecular Communication Networks for Viral Disease Analysis Using Deep Leaning Autoencoder.

Developing new treatments for emerging infectious diseases in infectious and noninfectious diseases has attracted a particular attention. The emergenc...

Deep Learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) With CT Images.

A novel coronavirus (COVID-19) recently emerged as an acute respiratory syndrome, and has caused a pneumonia outbreak world-widely. As the COVID-19 co...

The LHC Olympics 2020 a community challenge for anomaly detection in high energy physics.

A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly det...

Deep learning computer-aided detection system for pneumonia in febrile neutropenia patients: a diagnostic cohort study.

BACKGROUND: Diagnosis of pneumonia is critical in managing patients with febrile neutropenia (FN), however, chest X-ray (CXR) has limited performance ...

Choquet Integral and Coalition Game-Based Ensemble of Deep Learning Models for COVID-19 Screening From Chest X-Ray Images.

Under the present circumstances, when we are still under the threat of different strains of coronavirus, and since the most widely used method for COV...

Fine scale prediction of ecological community composition using a two-step sequential Machine Learning ensemble.

Prediction is one of the last frontiers in ecology. Indeed, predicting fine-scale species composition in natural systems is a complex challenge as mul...

Deep Learning-Based Sentiment Analysis of COVID-19 Vaccination Responses from Twitter Data.

The COVID-19 pandemic has had a devastating effect on many people, creating severe anxiety, fear, and complicated feelings or emotions. After the init...

Validation of expert system enhanced deep learning algorithm for automated screening for COVID-Pneumonia on chest X-rays.

SARS-CoV2 pandemic exposed the limitations of artificial intelligence based medical imaging systems. Earlier in the pandemic, the absence of sufficien...

Mild Adverse Events of Sputnik V Vaccine in Russia: Social Media Content Analysis of Telegram via Deep Learning.

BACKGROUND: There is a limited amount of data on the safety profile of the COVID-19 vector vaccine Gam-COVID-Vac (Sputnik V). Previous infodemiology s...

Machine Learning-based Voice Assessment for the Detection of Positive and Recovered COVID-19 Patients.

Many virological tests have been implemented during the Coronavirus Disease 2019 (COVID-19) pandemic for diagnostic purposes, but they appear unsuitab...

Automated Curb Recognition and Negotiation for Robotic Wheelchairs.

Common electric powered wheelchairs cannot safely negotiate architectural barriers (i.e., curbs) which could injure the user and damage the wheelchair...

UMLF-COVID: an unsupervised meta-learning model specifically designed to identify X-ray images of COVID-19 patients.

BACKGROUND: With the rapid spread of COVID-19 worldwide, quick screening for possible COVID-19 patients has become the focus of international research...

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...

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...

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...

[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...