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Semi-automated title-abstract screening using natural language processing and machine learning

Title-abstract screening in the preparation of a systematic review is a time-consuming task. Modern techniques of natural language processing and machine learning might allow partly automatization of title-abstract screening. In particular, clear guidance on how to proceed with these techniques in p...

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Main Authors: Pilz, Maximilian (Author) , Zimmermann, Samuel (Author) , Friedrichs, Juliane (Author) , Wördehoff, Enrica (Author) , Ronellenfitsch, Ulrich (Author) , Kieser, Meinhard (Author) , Vey, Johannes (Author)
Format: Article (Journal)
Language:English
Published: 1 November 2024
In: Systematic Reviews
Year: 2024, Volume: 13, Pages: 1-14
ISSN:2046-4053
DOI:10.1186/s13643-024-02688-w
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1186/s13643-024-02688-w
Verlag, kostenfrei, Volltext: http://dx.doi.org/10.25673/117797
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Author Notes:Maximilian Pilz, Samuel Zimmermann, Juliane Friedrichs, Enrica Wördehoff, Ulrich Ronellenfitsch, Meinhard Kieser and Johannes A. Vey
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Summary:Title-abstract screening in the preparation of a systematic review is a time-consuming task. Modern techniques of natural language processing and machine learning might allow partly automatization of title-abstract screening. In particular, clear guidance on how to proceed with these techniques in practice is of high relevance
Item Description:Gesehen am 15.04.2025
Physical Description:Online Resource
ISSN:2046-4053
DOI:10.1186/s13643-024-02688-w

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