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Article ; Online: Tools to support the automation of systematic reviews: a scoping review.

Khalil, Hanan / Ameen, Daniel / Zarnegar, Armita

Journal of clinical epidemiology

2021  Volume 144, Page(s) 22–42

Abstract: Objective: The objectives of this scoping review are to identify the reliability and validity of the available tools, their limitations and any recommendations to further improve the use of these tools.: Study design: A scoping review methodology was ...

Abstract Objective: The objectives of this scoping review are to identify the reliability and validity of the available tools, their limitations and any recommendations to further improve the use of these tools.
Study design: A scoping review methodology was followed to map the literature published on the challenges and solutions of conducting evidence synthesis using the JBI scoping review methodology.
Results: A total of 47 publications were included in the review. The current scoping review identified that LitSuggest, Rayyan, Abstractr, BIBOT, R software, RobotAnalyst, DistillerSR, ExaCT and NetMetaXL have potential to be used for the automation of systematic reviews. However, they are not without limitations. The review also identified other studies that employed algorithms that have not yet been developed into user friendly tools. Some of these algorithms showed high validity and reliability but their use is conditional on user knowledge of computer science and algorithms.
Conclusion: Abstract screening has reached maturity; data extraction is still an active area. Developing methods to semi-automate different steps of evidence synthesis via machine learning remains an important research direction. Also, it is important to move from the research prototypes currently available to professionally maintained platforms.
MeSH term(s) Automation ; Humans ; Machine Learning ; Reproducibility of Results ; Software ; Systematic Reviews as Topic
Language English
Publishing date 2021-12-08
Publishing country United States
Document type Journal Article ; Review
ZDB-ID 639306-8
ISSN 1878-5921 ; 0895-4356
ISSN (online) 1878-5921
ISSN 0895-4356
DOI 10.1016/j.jclinepi.2021.12.005
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bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
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