التفاصيل البيبلوغرافية
| العنوان: |
Building a Systematic Online Living Evidence Summary of COVID-19 Research |
| المؤلفون: |
Hair, Kaitlyn, Sena, Emily S., Wilson, Emma, Currie, Gillian, Macleod, Malcolm, Bahor, Zsanett, Sena, Chris, Ayder, Can, Liao, Jing, Tanriver Ayder, Ezgi, Ghanawi, Joly, Tsang, Anthony, Collins, Anne, Carstairs, Alice, Antar, Sarah, Drax, Katie, Neves, Kleber, Ottavi, Thomas, Chow, Yoke Yue, Henry, David, Selli, Cigdem, Fofana, Mariam, Rudnicki, Martina, Gabriel, Brendan, Pearl, Esther J, Kapoor, Simran S, Baginskaite, Julija, Shevade, Santosh, Chung, Alexandria, Przybylska, Marianna Antonia, Henshall, David E, Hajdu, Karina L�bo, McCann, Sarah, Sutherland, Catherine, Lubiana Alves, Tiago, Blacow, Rachel, Hood, Rebecca J., Soliman, Nadia, Harris, Alison, Swift, Stephanie L., Rackoll, Torsten, Percie du Sert, Nathalie, Waldron, Fergal, Macleod, Magnus, Moulson, Ruth, Low, Juin W., Rannikmae, Kristiina, Miller, Kirsten, Bannach-Brown, Alexandra, Kerr, Fiona, H�bert, Harry L, Gregory, Sarah, Shaw, Isaac William, Christides, Alexander, Alawady, Mohammed, Hillary, Robert, Clark, Alex, Jayasuriya, Natasha, Sives, Samantha, Nazzal, Ahmed, Jayasuriya, Nimesh, Sewell, Michael, Bertani, Rita, Fielding, Helen, Drury, Broc |
| بيانات النشر: |
European Association for Health Information and Libraries |
| سنة النشر: |
2021 |
| المجموعة: |
Edinburgh Napier Repository (Napier University Edinburgh) |
| مصطلحات موضوعية: |
COVID-19, evidence synthesis, machine learning, web application, database |
| الوصف: |
Throughout the global coronavirus pandemic, we have seen an unprecedented volume of COVID-19 researchpublications. This vast body of evidence continues to grow, making it difficult for research users to keep up with the pace of evolving research findings. To enable the synthesis of this evidence for timely use by researchers, policymakers, and other stakeholders, we developed an automated workflow to collect, categorise, and visualise the evidence from primary COVID-19 research studies. We trained a crowd of volunteer reviewers to annotate studies by relevance to COVID-19, study objectives, and methodological approaches. Using these human decisions, we are training machine learning classifiers and applying text-mining tools to continually categorise the findings and evaluate the quality of COVID-19 evidence. |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
English |
| تدمد: |
1841-0715 |
| العلاقة: |
http://researchrepository.napier.ac.uk/Output/2786196Test; https://napier-repository.worktribe.com/file/2786196/1/Building%20A%20Systematic%20Online%20Living%20Evidence%20Summary%20Of%20COVID-19%20ResearchTest |
| DOI: |
10.32384/jeahil17465 |
| الإتاحة: |
https://doi.org/10.32384/jeahil17465Test
https://napier-repository.worktribe.com/file/2786196/1/Building%20A%20Systematic%20Online%20Living%20Evidence%20Summary%20Of%20COVID-19%20ResearchTest
http://researchrepository.napier.ac.uk/Output/2786196Test |
| حقوق: |
openAccess ; http://creativecommons.org/licenses/by/4.0Test/ |
| رقم الانضمام: |
edsbas.815BA685 |
| قاعدة البيانات: |
BASE |
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