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Introducing RAPTOR: RevMan Parsing Tool for Reviewers
by
Shokraneh, Farhad
, Schmidt, Lena
, Adams, Clive E.
, Steinhausen, Kirsten
in
Automatic document classification
/ Automation
/ Biomedicine
/ Data extraction
/ Document classification
/ Health Sciences
/ Letter
/ Medicine
/ Medicine & Public Health
/ RevMan
/ Statistics for Life Sciences
/ Systematic reviews
2019
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Introducing RAPTOR: RevMan Parsing Tool for Reviewers
by
Shokraneh, Farhad
, Schmidt, Lena
, Adams, Clive E.
, Steinhausen, Kirsten
in
Automatic document classification
/ Automation
/ Biomedicine
/ Data extraction
/ Document classification
/ Health Sciences
/ Letter
/ Medicine
/ Medicine & Public Health
/ RevMan
/ Statistics for Life Sciences
/ Systematic reviews
2019
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Do you wish to request the book?
Introducing RAPTOR: RevMan Parsing Tool for Reviewers
by
Shokraneh, Farhad
, Schmidt, Lena
, Adams, Clive E.
, Steinhausen, Kirsten
in
Automatic document classification
/ Automation
/ Biomedicine
/ Data extraction
/ Document classification
/ Health Sciences
/ Letter
/ Medicine
/ Medicine & Public Health
/ RevMan
/ Statistics for Life Sciences
/ Systematic reviews
2019
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Journal Article
Introducing RAPTOR: RevMan Parsing Tool for Reviewers
2019
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Overview
Background
Much effort is made to ensure Cochrane reviews are based on reliably extracted data. There is a commitment to wide access to these data—for novel processing and/or reuse—but delivering this access is problematic.
Aim
To describe a proof-of-concept programme to extract, curate and structure data from Cochrane reviews.
Methods
One student of Applied Sciences (16 weeks full time), access to pre-publication review files and use of ‘Eclipse’ to create an open-access tool (RAPTOR) using the programming language Java.
Results
The final software batch processes hundreds of reviews in seconds, extracting all study data and automatically tidying and unifying presentation of data for return into the source review, reuse, or export for novel analyses.
Conclusions
This software, despite being limited, illustrates how the efforts of reviewers meticulously extracting study data can be improved, disseminated and reused with little additional effort.
Publisher
BioMed Central,BMC
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