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Purpose: Artificial intelligence (AI) techniques have been extensively utilized for diagnosing and prognosis of several diseases in recent years. This study identifies, appraises and synthesizes published studies on the use of AI for the…

Building AI models with trustworthiness is important especially in regulated areas such as healthcare. In tackling COVID-19, previous work uses convolutional neural networks as the backbone architecture, which has shown to be prone to…

In medical practice, the contribution of information technology can be considerable. Most of these practices include the images that medical assistance uses to identify different pathologies of the human body. One of them is X-ray images…

COVID-19 infection caused by SARS-CoV-2 pathogen is a catastrophic pandemic outbreak all over the world with exponential increasing of confirmed cases and, unfortunately, deaths. In this work we propose an AI-powered pipeline, based on the…

In this paper, we present the major results from the Covid Radiographic imaging System based on AI (Co.R.S.A.) project, which took place in Italy. This project aims to develop a state-of-the-art AI-based system for diagnosing Covid-19…

Biomedical imaging analysis combined with artificial intelligence (AI) methods has proven to be quite valuable in order to diagnose COVID-19. So far, various classification models have been used for diagnosing COVID-19. However,…

Coronavirus disease 2019 (COVID-19) is one of the most destructive pandemic after millennium, forcing the world to tackle a health crisis. Automated lung infections classification using chest X-ray (CXR) images could strengthen diagnostic…

The infection of respiratory coronavirus disease 2019 (COVID-19) starts with the upper respiratory tract and as the virus grows, the infection can progress to lungs and develop pneumonia. The conventional way of COVID-19 diagnosis is…

We found that the real time reverse transcription-polymerase chain reaction (RT-PCR) detection of viral RNA from sputum or nasopharyngeal swab has a relatively low positive rate in the early stage to determine COVID-19 (named by the World…

This paper proposed an ensemble of deep convolutional neural networks (CNN) based on EfficientNet, named ECOVNet, to detect COVID-19 using a large chest X-ray data set. At first, the open-access large chest X-ray collection is augmented,…

Chest X-rays remains to be the most common imaging modality used to diagnose lung diseases. However, they necessitate the interpretation of experts (radiologists and pulmonologists), who are few. This review paper investigates the use of…

Purpose: To answer the long-standing question of whether a model trained from a single clinical site can be generalized to external sites. Materials and Methods: 17,537 chest x-ray radiographs (CXRs) from 3,264 COVID-19-positive patients…

This paper is responding to the MIA-COV19 challenge to classify COVID from non-COVID based on CT lung images. The COVID-19 virus has devastated the world in the last eighteen months by infecting more than 182 million people and causing over…

In 2019, the world faced a new challenge: a COVID-19 disease caused by the novel coronavirus, SARS-CoV-2. The virus rapidly spread across the globe, leading to a high rate of mortality, which prompted health organizations to take measures…

Problem: Detecting COVID-19 from chest X-Ray (CXR) images has become one of the fastest and easiest methods for detecting COVID-19. However, the existing methods usually use supervised transfer learning from natural images as a pretraining…

With COVID-19 cases rising rapidly, deep learning has emerged as a promising diagnosis technique. However, identifying the most accurate models to characterize COVID-19 patients is challenging because comparing results obtained with…

The COVID-19 pandemic strained healthcare resources and prompted discussion about how machine learning can alleviate physician burdens and contribute to diagnosis. Chest x-rays (CXRs) are used for diagnosis of COVID-19, but few studies…

The novel corona virus (Covid-19) has introduced significant challenges due to its rapid spreading nature through respiratory transmission. As a result, there is a huge demand for Artificial Intelligence (AI) based quick disease diagnosis…

The COVID19 pandemic has had a detrimental impact on the health and welfare of the worlds population. An important strategy in the fight against COVID19 is the effective screening of infected patients, with one of the primary screening…

In the research, we developed a computer vision solution to support diagnostic radiology in differentiating between COVID-19 pneumonia, influenza virus pneumonia, and normal biomarkers. The chest radiograph appearance of COVID-19 pneumonia…