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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| Hauptverfasser: | , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
1 November 2024
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| In: |
Systematic Reviews
Year: 2024, Jahrgang: 13, Pages: 1-14 |
| ISSN: | 2046-4053 |
| DOI: | 10.1186/s13643-024-02688-w |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1186/s13643-024-02688-w Verlag, kostenfrei, Volltext: http://dx.doi.org/10.25673/117797 |
| Verfasserangaben: | Maximilian Pilz, Samuel Zimmermann, Juliane Friedrichs, Enrica Wördehoff, Ulrich Ronellenfitsch, Meinhard Kieser and Johannes A. Vey |
| Zusammenfassung: | 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 |
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| Beschreibung: | Gesehen am 15.04.2025 |
| Beschreibung: | Online Resource |
| ISSN: | 2046-4053 |
| DOI: | 10.1186/s13643-024-02688-w |