<div class="csl-bib-body">
<div class="csl-entry">Brassey, J., Price, C., Edwards, J., Zlabinger, M., Bampoulidis, A., & Hanbury, A. (2021). Developing a fully automated evidence synthesis tool for identifying, assessing and collating the evidence. <i>BMJ Evidence-Based Medicine</i>, <i>26</i>(1), 24–27. https://doi.org/10.1136/bmjebm-2018-111126</div>
</div>
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dc.identifier.issn
2515-446X
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/144063
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dc.description.abstract
Evidence synthesis is a key element of evidence-based medicine. However, it is currently hampered by being labour intensive meaning that many trials are not incorporated into robust evidence syntheses and that many are out of date. To overcome this, a variety of techniques are being explored, including using automation technology. Here, we describe a fully automated evidence synthesis system for intervention studies, one that identifies all the relevant evidence, assesses the evidence for reliability and collates it to estimate the relative effectiveness of an intervention. Techniques used include machine learning, natural language processing and rule-based systems. Results are visualised using modern visualisation techniques. We believe this to be the first, publicly available, automated evidence synthesis system: an evidence mapping tool that synthesises evidence on the fly.
en
dc.language.iso
en
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dc.publisher
BMJ PUBLISHING GROUP
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dc.relation.ispartof
BMJ Evidence-Based Medicine
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dc.subject
General Medicine
en
dc.title
Developing a fully automated evidence synthesis tool for identifying, assessing and collating the evidence
en
dc.type
Artikel
de
dc.type
Article
en
dc.description.startpage
24
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dc.description.endpage
27
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dc.type.category
Original Research Article
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tuw.container.volume
26
-
tuw.container.issue
1
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tuw.journal.peerreviewed
true
-
tuw.peerreviewed
true
-
wb.publication.intCoWork
International Co-publication
-
tuw.researchTopic.id
I4a
-
tuw.researchTopic.name
Information Systems Engineering
-
tuw.researchTopic.value
100
-
dcterms.isPartOf.title
BMJ Evidence-Based Medicine
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tuw.publication.orgunit
E194-04 - Forschungsbereich Data Science
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tuw.publication.orgunit
E194-01 - Forschungsbereich Software Engineering
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tuw.publisher.doi
10.1136/bmjebm-2018-111126
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dc.date.onlinefirst
2019
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dc.identifier.eissn
2515-4478
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dc.description.numberOfPages
4
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tuw.author.orcid
0000-0002-7812-6311
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wb.sci
true
-
wb.sciencebranch
Informatik
-
wb.sciencebranch.oefos
1020
-
wb.facultyfocus
Information Systems Engineering (ISE)
de
wb.facultyfocus
Information Systems Engineering (ISE)
en
wb.facultyfocus.faculty
E180
-
item.grantfulltext
none
-
item.openairetype
research article
-
item.openairecristype
http://purl.org/coar/resource_type/c_2df8fbb1
-
item.languageiso639-1
en
-
item.fulltext
no Fulltext
-
item.cerifentitytype
Publications
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crisitem.author.dept
E194-04 - Forschungsbereich Data Science
-
crisitem.author.dept
E194 - Institut für Information Systems Engineering
-
crisitem.author.dept
E194-04 - Forschungsbereich Data Science
-
crisitem.author.orcid
0000-0002-7149-5843
-
crisitem.author.parentorg
E194 - Institut für Information Systems Engineering
-
crisitem.author.parentorg
E180 - Fakultät für Informatik
-
crisitem.author.parentorg
E194 - Institut für Information Systems Engineering