Related papers: Constructing the CORD-19 Vaccine Dataset
Objective: To discover candidate drugs to repurpose for COVID-19 using literature-derived knowledge and knowledge graph completion methods. Methods: We propose a novel, integrative, and neural network-based literature-based discovery (LBD)…
To design effective vaccine policies, policymakers need detailed data about who has been vaccinated, who is holding out, and why. However, existing data in the US are insufficient: reported vaccination rates are often delayed or missing,…
The COVID-19 pandemic swept across the world rapidly, infecting millions of people. An efficient tool that can accurately recognize important clinical concepts of COVID-19 from free text in electronic health records (EHRs) will be valuable…
This paper explains the scalable methods used for extracting and analyzing the Covid-19 vaccine data. Using Big Data such as Hadoop and Hive, we collect and analyze the massive data set of the confirmed, the fatality, and the vaccination…
The COVID-19 pandemic has made a huge global impact and cost millions of lives. As COVID-19 vaccines were rolled out, they were quickly met with widespread hesitancy. To address the concerns of hesitant people, we launched VIRA, a public…
Although the recent rise and uptake of COVID-19 vaccines in the United States has been encouraging, there continues to be significant vaccine hesitancy in various geographic and demographic clusters of the adult population. Surveys, such as…
This report describes the participation of two Danish universities, University of Copenhagen and Aalborg University, in the international search engine competition on COVID-19 (the 2020 TREC-COVID Challenge) organised by the U.S. National…
We are developing semantic visualization techniques in order to enhance exploration and enable discovery over large datasets of complex networks of relations. Semantic visualization is a method of enabling exploration and discovery over…
Much of human knowledge sits in large databases of unstructured text. Leveraging this knowledge requires algorithms that extract and record metadata on unstructured text documents. Assigning topics to documents will enable intelligent…
The world has seen in 2020 an unprecedented global outbreak of SARS-CoV-2, a new strain of coronavirus, causing the COVID-19 pandemic, and radically changing our lives and work conditions. Many scientists are working tirelessly to find a…
Automated information extraction with natural language processing (NLP) tools is required to gain systematic insights from the large number of COVID-19 publications, reports and social media posts, which far exceed human processing…
Despite ample supply of COVID-19 vaccines, the proportion of fully vaccinated individuals remains suboptimal across much of the US. Rapid vaccination of additional people will prevent new infections among both the unvaccinated and the…
The novel corona-virus disease (also known as COVID-19) has led to a pandemic, impacting more than 200 countries across the globe. With its global impact, COVID-19 has become a major concern of people almost everywhere, and therefore there…
The COVID-19 pandemic continues to bring up various topics discussed or debated on social media. In order to explore the impact of pandemics on people's lives, it is crucial to understand the public's concerns and attitudes towards…
Background Medical and life science research generates millions of publications, and it is a great challenge for researchers to utilize this information in full since its scale and complexity greatly surpasses human reading capabilities.…
Automatic Text Categorization (TC) is a complex and useful task for many natural language applications, and is usually performed through the use of a set of manually classified documents, a training collection. We suggest the utilization of…
Legal practitioners and judicial institutions face an ever-growing volume of case-law documents characterised by formalised language, lengthy sentence structures, and highly specialised terminology, making manual triage both time-consuming…
We are presenting COVID-19Base, a knowledgebase highlighting the biomedical entities related to COVID-19 disease based on literature mining. To develop COVID-19Base, we mine the information from publicly available scientific literature and…
Documents often contain complex physical structures, which make the Document Layout Analysis (DLA) task challenging. As a pre-processing step for content extraction, DLA has the potential to capture rich information in historical or…
Increasing number of COVID-19 research literatures cause new challenges in effective literature screening and COVID-19 domain knowledge aware Information Retrieval. To tackle the challenges, we demonstrate two tasks along withsolutions,…