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21 results for “CORD-19”
Softcite software mention extraction from the CORD-19 publications
<p><strong>Softcite software mention extraction from the CORD-19 publications </strong></p> <p>This dataset is the result of the extraction of software mentions from the set of publications of the CORD-19 corpus (<a href="https://allenai.org/data/cord-19">https://allenai.org/data/cord-19</a>) by the Softcite software recognizer (SciBERT-CRF fine-tuned model), see <a href="https://github.com/ourresearch/software-mentions">https://github.com/ourresearch/software-mentions</a>.</p> <p>The CORD-19 version used for this dataset is the one dated <strong>2021-07-26,</strong> using the <em>metadata.csv</em> file only. We re-harvested the PDF with <a href="https://github.com/kermitt2/article-dataset-builder">https://github.com/kermitt2/article-dataset-builder</a> in order to also extract coordinates of software mentions in the PDF and to take advantage of the latest version of GROBID to produce better full text extraction from PDF. We also harvested 61,230 full-texts more than the standard CORD-19 distribution.</p> <p>Note that this is the third version of this dataset (version 0.3.0). The previous Softcite software mention extraction from the CORD-19 was based on 2020-09-11 and 2021-03-22 versions. The new version cover a larger set of documents and is using an improved version of the extraction tools.</p> <p><strong>Data format </strong></p> <p>The extraction consists of 3 JSON files:</p> <p><strong>annotations.jsonl</strong> contains the individual software annotations including <em>software name</em> and possible attached attributes (<em>publisher</em>, <em>URL</em> and <em>version</em>). Each annotation is associated with coordinates expressed as bounding boxes in the original PDF. See <a href="https://grobid.readthedocs.io/en/latest/Coordinates-in-PDF/">Coordinates of structures in the original PDF</a> for more details on the coordinate format.</p> <p>The context of citation is the sentence where the software name and its attributes are extracted. It is added to the JSON structure (field <em>context</em>), as well as the identifier of the document where the annotation belongs (field <em>document</em>, pointing to entries available in <em>documents.json</em>) and a list of bibliographical references attached to the software name (field <em>references</em>, pointing to entries available in <em>references.json</em>, with the used reference marker string). See <a href="https://github.com/ourresearch/software-mentions">https://github.com/ourresearch/software-mentions</a> for more details on the extracted attributes.</p> <p>If the software name was sucessfully disambiguated against WikiData ("entity linking"), it appears in the field <em>wikidataId</em> as Wikidata entity identifier and in the field <em>wikipediaExternalRef</em> as a Wikipedia PageID from the English Wikipedia. Entity linking is realized with <a href="https://github.com/kermitt2/entity-fishing">entity-fishing</a>.</p> <p><strong>documents.jsonl</strong> contains the metadata of the all the CORD-19 documents containing at least one software annotation. The metadata are given as a CrossRef JSON structure. The abstract should be included in the metadata most of the time, as well as some complements extracted by GROBID directly from the PDF. In addition, the size of the pages and the unique file path to the PDF can be found to allow annotations directly on the PDF (see <a href="https://grobid.readthedocs.io/en/latest/Coordinates-in-PDF/">Coordinates of structures in the original PDF</a> for more details on the PDF annotation display mechanism).</p> <p><strong>references.jsonl </strong>contains the parsed reference entries associated to software mentions. These references are given in the field <em>tei</em> encoded in the XML TEI format of GROBID extraction. The extracted raw references have been matched against CrossRef to get a DOI and more complete metadata with <a href="https://github.com/kermitt2/biblio-glutton">biblio-glutton</a>.</p> <p><strong>Statistics</strong></p> <p>CORD-19 version: 2021-07-26</p> <p>- total Open Access full texts: 296,686<br> - with at least one software mention: 115,073</p> <p>- total software name annotations: 652,518<br> - with linked Wikidata ID: 231,599</p> <p>- associated field <br> - publisher: 107,421<br> - version: 188,724<br> - URL: 59,366<br> - references: 230,145</p> <p>- associated bibliographical references: 92,573<br> - references with matched DOI: 49,350<br> - references with matched PMID: 32,895<br> - references with matched PMC ID: 18,741</p> <p><strong>License and acknowledgements</strong></p> <p>This dataset is licensed under a Creative Commons Attribution 4.0 International License.</p> <p>We thank the Alfred P. Sloan Foundation and of the Gordon and Betty Moore Foundation for supporting this work.</p>
CORD-19 Named Entities Knowledge Graph (CORD19-NEKG)
<p>CORD-19 Named Entities Knowledge Graph (CORD19-NEKG) is an RDF dataset describing named entities identified in the scholarly articles of the <a href="https://www.semanticscholar.org/cord19">COVID-19 Open Research Dataset</a> (CORD-19), a resource of over 47,000 articles about COVID-19 and the coronavirus family of viruses.</p> <p>Homepage: https://github.com/Wimmics/cord19-nekg</p> <p>License: see LICENCE file in the dataset.</p>
CORD-19_ scite_citation_tallies+contexts
<pre>Update: As of March 27, 2020 we have now analyzed 31,527 distinct sources (articles and preprints) from the most recent CORD-19 data (<a href="https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge/version/4">https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge/version/4</a>. We're releasing citation tallies for these sources (covid-source-tallies 32720.csv). We're also releasing citation statements and classifications from these documents for open articles, which includes 1,682,216 out of the total 1,779,024 extracted. On March 20, 2020 we have analyzed 20,268 out of the 21,792 DOIS available from the <a href="https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge">CORD-19 data set</a>. Of these documents we found citations citing 16,775 of them, and the classifications for these citations are included in covid-source-tallies.csv. covid-citations.csv includes all citations we have from all of the ~20k documents we have processed. This file is truncated to make sure it only includes openly available documents. The tallies however are not limited by this, and it is the full set relating to all source documents scite has processed.</pre>
Drugs, Diseases, Genes and Proteins in the CORD-19 Corpus
<p>The BioNER+BioNEN system described in the paper "<strong><em>An Overview of Drugs, Diseases, Genes and Proteins in the CORD-19 Corpus</em></strong>", <em>Badenes-Olmedo, Carlos et. al, (2022)</em> was used to identify and normalize the drugs, diseases and genetic-related terms mentioned in the CORD-19 corpus (January 2022 Edition). Entity recognition and normalization was done for each paragraph of the scientific article. A first group of labels is created to identify the medical terms as they appear in the text (i.e. <em>diseases_ss</em>, <em>chemicals_ss</em>, <em>genetics_ss</em>), and in a standardized way (i.e. <em>disease_terms_ss</em>, <em>chemical_terms_ss</em>, <em>genetic_terms_ss</em>). In the case of diseases and genes/proteins, a predefined category is also established during the normalization process (i.e. <em>disease_types_ss</em>, <em>genetic_types_ss</em> ). The following group of labels contains the codes for each of the classification systems described in Section 3 (i.e. <em>mesh_codes_ss</em>, <em>atc_codes_ss</em>, <em>cid_codes_ss</em>, <em>doid_codes_ss</em>, <em>cui_codes_ss</em>, <em>icd10_codes_ss</em>, <em>icd9_codes_ss</em>, <em>gard_codes_ss</em>, <em>snomed_codes_ss</em>, <em>nci_codes_ss</em>, <em>ncbi_codes_ss</em>, <em>uniprot_codes_ss</em>). The suffix <em>_ss</em> in all tags indicates that the format is a textual list (i.e. string sequence).</p>
Safety and Efficacy of Umbilical Cord Mesenchymal Stem Cell Exosomes in Treating Chronic Cough After COVID-19
ClinicalTrials.gov study NCT05808400. IPD Sharing: NO. Countries: 1. Publications: 13.
Treatment With Human Umbilical Cord-derived Mesenchymal Stem Cells for Severe Corona Virus Disease 2019 (COVID-19)
ClinicalTrials.gov study NCT04288102. IPD Sharing: YES. Countries: 1. Publications: 4.
COVID-19 Open Research Dataset (CORD-19)
<p><strong>Important</strong>: This dataset is updated regularly and the latest version for download can be found <a href="https://www.semanticscholar.org/cord19/download">here</a>.</p> <p>In response to the COVID-19 pandemic, the <a href="https://allenai.org/">Allen Institute for AI</a> has partnered with leading research groups to prepare and distribute the COVID-19 Open Research Dataset (CORD-19), a free resource of scholarly articles, including full text content, about COVID-19 and the coronavirus family of viruses for use by the global research community.</p> <p>This dataset is intended to mobilize researchers to apply recent advances in natural language processing to generate new insights in support of the fight against this infectious disease. The corpus will be updated weekly as new research is published in peer-reviewed publications and archival services like <a href="https://www.biorxiv.org/">bioRxiv</a>, <a href="https://www.medrxiv.org/">medRxiv</a>, and others.</p> <p>By downloading this dataset you are agreeing to the Dataset license. Specific licensing information for individual articles in the dataset is available in the metadata file.</p> <p>Additional licensing information is available on the <a href="https://www.ncbi.nlm.nih.gov/pmc/tools/openftlist/">PMC website</a>, <a href="https://www.medrxiv.org/submit-a-manuscript">medRxiv website</a> and <a href="https://www.biorxiv.org/about-biorxiv">bioRxiv website</a>.</p> <p><strong>Dataset content:</strong></p> <ul> <li>Commercial use subset</li> <li>Non-commercial use subset</li> <li>PMC custom license subset</li> <li>bioRxiv/medRxiv subset (pre-prints that are not peer reviewed)</li> <li>Metadata file</li> <li>Readme</li> </ul> <p>Each paper is represented as a single JSON object (see schema file for details).</p> <p><strong>Description:</strong></p> <p>The dataset contains all COVID-19 and coronavirus-related research (e.g. SARS, MERS, etc.) from the following sources:</p> <ul> <li>PubMed's PMC open access corpus using this <a href="https://www.ncbi.nlm.nih.gov/pmc/?term=%22COVID-19%22+OR+Coronavirus+OR+%22Corona+virus%22+OR+%222019-nCoV%22+OR+%22SARS-CoV%22+OR+%22MERS-CoV%22+OR+%E2%80%9CSevere+Acute+Respiratory+Syndrome%E2%80%9D+OR+%E2%80%9CMiddle+East+Respiratory+Syndrome%E2%80%9D">query</a> (COVID-19 and coronavirus research)</li> <li>Additional COVID-19 research articles from a corpus maintained by the <a href="https://www.who.int/emergencies/diseases/novel-coronavirus-2019/global-research-on-novel-coronavirus-2019-ncov">WHO</a></li> <li>bioRxiv and medRxiv pre-prints using the same query as PMC (COVID-19 and coronavirus research)</li> </ul> <p>We also provide a comprehensive metadata file of coronavirus and COVID-19 research articles with links to <a href="https://www.ncbi.nlm.nih.gov/pmc/?term=%22COVID-19%22+OR+Coronavirus+OR+%22Corona+virus%22+OR+%222019-nCoV%22+OR+%22SARS-CoV%22+OR+%22MERS-CoV%22+OR+%E2%80%9CSevere+Acute+Respiratory+Syndrome%E2%80%9D+OR+%E2%80%9CMiddle+East+Respiratory+Syndrome%E2%80%9D">PubMed</a>, <a href="https://aka.ms/AA7q3eb">Microsoft Academic</a> and the <a href="https://www.who.int/emergencies/diseases/novel-coronavirus-2019/global-research-on-novel-coronavirus-2019-ncov">WHO COVID-19 database of publications</a> (includes articles without open access full text).</p> <p>We recommend using metadata from the comprehensive file when available, instead of parsed metadata in the dataset. Please note the dataset may contain multiple entries for individual PMC IDs in cases when supplementary materials are available.</p> <p>This repository is linked to the WHO database of publications on coronavirus disease and other resources, such as Microsoft Academic Graph, PubMed, and Semantic Scholar. A coalition including the <a href="https://chanzuckerberg.com/">Chan Zuckerberg Initiative</a>, Georgetown University’s <a href="https://cset.georgetown.edu/">Center for Security and Emerging Technology</a>, <a href="https://www.microsoft.com/en-us/research/">Microsoft Research</a>, and the <a href="https://www.nlm.nih.gov/">National Library of Medicine</a> of the National Institutes of Health came together to provide this service.</p> <p><strong>Citation:</strong></p> <p>When including CORD-19 data in a publication or redistribution, please cite our <a href="https://www.semanticscholar.org/paper/263db91cea260ca775cdbc482bca5392815c0533">arXiv pre-print</a>.</p> <p>The <a href="https://allenai.org/">Allen Institute for AI</a> and particularly the Semantic Scholar team will continue to provide updates to this dataset as the situation evolves and new research is released.</p>
CORD-19 Software Mentions
Open the record for dataset details and reuse information.
Study of Human Umbilical Cord Mesenchymal Stem Cells in the Treatment of Severe COVID-19
ClinicalTrials.gov study NCT04273646. IPD Sharing: NO. Countries: 1. Publications: 0.
Using PRP and Cord Blood in Treatment of Covid -19
ClinicalTrials.gov study NCT04393415. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evaluate the Safety and Efficacy of Allogeneic Umbilical Cord Mesenchymal Stem Cells in Patients With COVID-19
ClinicalTrials.gov study NCT05501418. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Umbilical Cord Lining Stem Cells (ULSC) in Patients With COVID-19 ARDS
ClinicalTrials.gov study NCT04494386. IPD Sharing: NO. Countries: 1. Publications: 0.
Clinical Trial of Allogeneic Mesenchymal Cells From Umbilical Cord Tissue in Patients With COVID-19
ClinicalTrials.gov study NCT04366271. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Efficacy and Safety of Umbilical Cord Mesenchymal Stem Cells in the Treatment of Long COVID-19
ClinicalTrials.gov study NCT05719012. IPD Sharing: NO. Countries: 1. Publications: 0.
Correlation of Antibody Response to COVID-19 Vaccination in Pregnant Woman and Transplacental Passage Into Cord Blood.
ClinicalTrials.gov study NCT06259656. IPD Sharing: NO. Countries: 1. Publications: 0.
Treatment of Respiratory Complications Associated With COVID-19 Using Umbilical Cord Mesenchymal Stromal Cells
ClinicalTrials.gov study NCT04869397. IPD Sharing: Not stated. Countries: 1. Publications: 0.
COVD-19 infection during pregnancy induces a hematopoietic stem cell signature in cord blood fetal cells
GEO Series GSE224063. Homo sapiens. 17 samples. Type: Expression profiling by high throughput sequencing.
Covid-19 Infection During Pregnancy Induces Differential Gene Expression in Human Cord Blood Cells from Term Neonates
GEO Series GSE195938. Homo sapiens. 16 samples. Type: Expression profiling by array.
kg-covid-19 graph in KGX TSV format, built on Sep 1, 2020, with no CORD-19 data
<p>KG-COVID-19 graph in KGX TSV format, built on Sep 1, 2020, with no CORD-19 data</p>
Umbilical Cord Tissue (UC) Derived Mesenchymal Stem Cells (MSCs) Versus Placebo to Treat Acute Pulmonary Inflammation Due to COVID-19
ClinicalTrials.gov study NCT04490486. IPD Sharing: NO. Countries: 0. Publications: 0.
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