BaySREn-package: A package to automatise citation collection and screening in...
In bakaburg1/BaySREn: BaySREn. An R package to automatise citation collection and screening in Systematic Reviews. Based on Bayesian active machine learning
BaySREn-package R Documentation
A package to automatise citation collection and screening in Systematic
Reviews
Description
Secondary research is of paramount importance to summarise the
latest developments in every research field. Nevertheless, conducting a
structured collection and analysis of literature (i.e., a Systematic Review)
is becoming exceedingly demanding in terms of time and human resources.We
propose an integrated framework that streamlines and automates the citation
data collection and title/abstract screening phases of Systematic Reviews,
limiting human intervention to a minimum. The framework employs automatic
citation collection from online scientific databases and importation tools to
import citation data collected manually; it uses a Bayesian active
machine-learning algorithm to screen relevant citation, requiring human input
only at the beginning of the process and to review uncertain classifications.
Finally, the framework provides a tool to generate search queries with online
scientific databases based on an already labelled corpus of citation data.
bakaburg1/BaySREn documentation built on March 30, 2022, 12:16 a.m.
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| BaySREn-package | R Documentation |
A package to automatise citation collection and screening in Systematic Reviews
Description
Secondary research is of paramount importance to summarise the latest developments in every research field. Nevertheless, conducting a structured collection and analysis of literature (i.e., a Systematic Review) is becoming exceedingly demanding in terms of time and human resources.We propose an integrated framework that streamlines and automates the citation data collection and title/abstract screening phases of Systematic Reviews, limiting human intervention to a minimum. The framework employs automatic citation collection from online scientific databases and importation tools to import citation data collected manually; it uses a Bayesian active machine-learning algorithm to screen relevant citation, requiring human input only at the beginning of the process and to review uncertain classifications. Finally, the framework provides a tool to generate search queries with online scientific databases based on an already labelled corpus of citation data.
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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