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Filtrage par: Language English Supprimer la restriction Language: English Collections Data Sets for HDSR publication "Convergence in Viral Epidemic Research: Using Natural Language Processing to Define Network Bridges in the Bench-Bedside-Population Paradigm" Supprimer la restriction Collections: Data Sets for HDSR publication "Convergence in Viral Epidemic Research: Using Natural Language Processing to Define Network Bridges in the Bench-Bedside-Population Paradigm"

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  • APPENDIX D: Topic Network Maps for a Random 10k Documents & the Complete CORD-19 Dataset

    Document thumbnail: APPENDIX D: Topic Network Maps for a Random 10k Documents & the Complete CORD-19 Dataset
    Type:
    Document
    Description/Abstract:
    All models and corresponding network visualizations are generated from documents in the CORD-19 dataset as of July 14, 2020. All annotations in red were added by the research team. Note: These topic models are included here as additional reference and to append links to interactive versions on the Digital Scholarship Center’s machine learning platform for further exploration.
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    02/26/2021
    Date Modified:
    02/26/2021
    Date Created:
    2020
    License:
    CC0 1.0 Universal

  • APPENDIX C: Non-Coronaviridae Topic Network Maps [HIV, ZIKA, H1N1, EBOLA]

    Document thumbnail: APPENDIX C: Non-Coronaviridae Topic Network Maps [HIV, ZIKA, H1N1, EBOLA]
    Type:
    Document
    Description/Abstract:
    All models and corresponding network visualizations are generated from virus related documents in the CORD-19 dataset as of July 14, 2020. All annotations in red were added by the research team. Note: Certain Non-Coronaviridae topic models are included in the text of this article and are included here only as additional reference and to append links to interactive versions on the Digital Scholarship Center’s machine learning platform for further exploration.
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    02/26/2021
    Date Modified:
    02/26/2021
    Date Created:
    2020
    License:
    CC0 1.0 Universal

  • APPENDIX B: Coronaviridae Topic Network Maps [SARS, MERS, COVID-19]

    Document thumbnail: APPENDIX B: Coronaviridae Topic Network Maps [SARS, MERS, COVID-19]
    Type:
    Document
    Description/Abstract:
    All models and corresponding network visualizations are generated from virus related documents in the CORD-19 dataset as of July, 2020. All annotations in red were added by the research team. Note: Coronavirus topic models are included in the text of this article and are included here only as additional reference and to append links to interactive versions on the Digital Scholarship Center’s machine learning platform for further exploration.
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    02/26/2021
    Date Modified:
    02/26/2021
    License:
    CC0 1.0 Universal

  • COVID 19 literature NLP models – Viral outbreak topic tuning

    Dataset thumbnail: COVID 19 literature NLP models – Viral outbreak topic tuning
    Type:
    Dataset
    Description/Abstract:
    The data sets were derived from coronavirus related scientific literature using the CORD-19 dataset released by the Allen Institute of Artificial Intelligence as of July 14, 2020, using the Elasticsearch engine hosted by the Digital Scholarship Center (DSC). Through indexing the full-text and the metadata of the article corpus, the research team generated a full-corpus model and 7 different models corresponding to key viral outbreaks from the past several decades' coronaviruses (SARS-CoV, MERS-CoV, and SARS- CoV-2) and non-coronaviruses (HIV, Zika, H1N1, and Ebola). The targeted subsets of the articles used two or more occurrences of virus-specific keywords drawn from conventions established by the World Health Organization.
    Creator/Author:
    Koshoffer, Amy; Wu, Danny; Latessa, Jenny; Kannayyagar, Suraj; Luken, Sally; McCabe, Erin; Edgerton, Ezra; Washington, Dorcas; Lee, James; Powers, Margaret, and Hagedorn, Philip
    Submitter:
    Amy Koshoffer
    Date Uploaded:
    10/30/2020
    Date Modified:
    11/05/2020
    Date Created:
    2020-07
    License:
    CC0 1.0 Universal

  • COVID 19 literature NLP models – Viral outbreak models formatted

    Dataset thumbnail: COVID 19 literature NLP models – Viral outbreak models formatted
    Type:
    Dataset
    Description/Abstract:
    The data sets were derived from coronavirus related scientific literature using the CORD-19 dataset released by the Allen Institute of Artificial Intelligence as of July 14, 2020, using the Elasticsearch engine hosted by the Digital Scholarship Center (DSC). Through indexing the full-text and the metadata of the article corpus, the research team generated a full-corpus model and 7 different models corresponding to key viral outbreaks from the past several decades' coronaviruses (SARS-CoV, MERS-CoV, and SARS- CoV-2) and non-coronaviruses (HIV, Zika, H1N1, and Ebola). The targeted subsets of the articles used two or more occurrences of virus-specific keywords drawn from conventions established by the World Health Organization.
    Creator/Author:
    Koshoffer, Amy; Hagedorn, Philip ; Latessa, Jenny; Lee, James; Power, Margaret; Luken, Sally; McCabe, Erin; Wu. Danny; Washington, Dorcas; Kannayyagar, Suraj, and Edgerton, Ezra
    Submitter:
    Amy Koshoffer
    Date Uploaded:
    10/29/2020
    Date Modified:
    11/05/2020
    Date Created:
    2020-07
    License:
    CC0 1.0 Universal

  • COVID 19 literature NLP models - Viral outbreak model centrality files

    Dataset thumbnail: COVID 19 literature NLP models - Viral outbreak model centrality files
    Type:
    Dataset
    Description/Abstract:
    The data sets were derived from coronavirus related scientific literature using the CORD-19 dataset released by the Allen Institute of Artificial Intelligence as of July 14, 2020, using the Elasticsearch engine hosted by the Digital Scholarship Center (DSC). Through indexing the full-text and the metadata of the article corpus, the research team generated a full-corpus model and 7 different models corresponding to key viral outbreaks from the past several decades' coronaviruses (SARS-CoV, MERS-CoV, and SARS- CoV-2) and non-coronaviruses (HIV, Zika, H1N1, and Ebola). The targeted subsets of the articles used two or more occurrences of virus-specific keywords drawn from conventions established by the World Health Organization.
    Creator/Author:
    Koshoffer, Amy; Wu, Danny; Latessa, Jenny; Lee, James; Luken, Sally; McCabe, Erin; Edgerton, Ezra; Washington, Dorcas; Kannayyagar, Suraj, and Powers, Margaret
    Submitter:
    Amy Koshoffer
    Date Uploaded:
    10/29/2020
    Date Modified:
    11/05/2020
    Date Created:
    2020-07
    License:
    CC0 1.0 Universal