Related papers: Reproducibility of COVID-19 pre-prints

In this paper, we present ArCOV-19, an Arabic COVID-19 Twitter dataset that spans one year, covering the period from 27th of January 2020 till 31st of January 2021. ArCOV-19 is the first publicly-available Arabic Twitter dataset covering…

As scientists worldwide search for answers to the overwhelmingly unknown behind the deadly pandemic, the literature concerning COVID-19 has been growing exponentially. Keeping abreast of the body of literature at such a rapidly advancing…

The COVID-19 pandemic accelerated the use of preprints, aiding rapid research dissemination but also facilitating the spread of misinformation. This study analyzes media coverage of preprints from 2014 to 2023, revealing a significant…

The COVID-19 pandemic catalyzed the rapid dissemination of papers and preprints investigating the disease and its associated virus, SARS-CoV-2. The multifaceted nature of COVID-19 demands a multidisciplinary approach, but the urgency of the…

Background. After a year and half and over 4 million deaths, the COVID-19 pandemic continues to be widespread, and its related topics continue to dominate the global media. Although COVID-19 diagnoses have been well monitored, neither the…

We present the Neural Covidex, a search engine that exploits the latest neural ranking architectures to provide information access to the COVID-19 Open Research Dataset curated by the Allen Institute for AI. This web application exists as…

The outbreak of COVID-19 has shocked the entire world with its fairly rapid spread and has challenged different sectors. One of the most effective ways to limit its spread is the early and accurate diagnosing infected patients. Medical…

The possibility to use widespread and simple chest X-ray (CXR) imaging for early screening of COVID-19 patients is attracting much interest from both the clinical and the AI community. In this study we provide insights and also raise…

Amid the COVID-19 pandemic, while the world sought solutions, some scholars exploited the situation for personal gains through deceptive studies and manipulated data. This paper presents the extent of 400 retracted COVID-19 papers listed by…

LitCovid (https://www.ncbi.nlm.nih.gov/research/coronavirus/), first launched in February 2020, is a first-of-its-kind literature hub for tracking up-to-date published research on COVID-19. The number of articles in LitCovid has increased…

From March 23rd, the data for the recovered cases of COVID-19 are missing from the standard repository maintained by the Johns Hopkins University in collaboration with the WHO. But since data concerning recovered patients are extremely…

During the outbreak time of COVID-19, computed tomography (CT) is a useful manner for diagnosing COVID-19 patients. Due to privacy issues, publicly available COVID-19 CT datasets are highly difficult to obtain, which hinders the research…

The widely spread CoronaVirus Disease (COVID)-19 is one of the worst infectious disease outbreaks in history and has become an emergency of primary international concern. As the pandemic evolves, academic communities have been actively…

Across the world's coronavirus disease 2019 (COVID-19) hot spots, the need to streamline patient diagnosis and management has become more pressing than ever. As one of the main imaging tools, chest X-rays (CXRs) are common, fast,…

Objective: The novel coronavirus COVID-19 outbreak rapidly evolved into pandemic. Global research efforts focus on this topic and with the collaboration of the scientific journals publication industry produced more than 16,000 related…

The global pandemic has made it more important than ever to quickly and accurately retrieve relevant scientific literature for effective consumption by researchers in a wide range of fields. We provide an analysis of several multi-label…

On February 2, 2020, the World Health Organization declared a COVID-19 social media "infodemic", with special attention to misinformation -- frequently understood as false claims. To understand the infodemic's scope and scale, we analyzed…

Double-blind conferences have engaged in debates over whether to allow authors to post their papers online on arXiv or elsewhere during the review process. Independently, some authors of research papers face the dilemma of whether to put…

In the midst of the coronavirus disease 2019 (COVID-19) outbreak, chest X-ray (CXR) imaging is playing an important role in the diagnosis and monitoring of patients with COVID-19. Machine learning solutions have been shown to be useful for…

Epidemiologist, Scientists, Statisticians, Historians, Data engineers and Data scientists are working on finding descriptive models and theories to explain COVID-19 expansion phenomena or on building analytics predictive models for learning…