The Automated Systematic Search Deduplicator (ASySD): a rapid, open-source, interoperable tool to remove duplicate citations in biomedical systematic reviews.
Automation tools
Bibliographic database
Citation manager
Deduplication
EndNote
Living systematic reviews
Systematic reviews
Systematic search
Journal
BMC biology
ISSN: 1741-7007
Titre abrégé: BMC Biol
Pays: England
ID NLM: 101190720
Informations de publication
Date de publication:
07 09 2023
07 09 2023
Historique:
received:
14
04
2022
accepted:
21
08
2023
medline:
8
9
2023
pubmed:
7
9
2023
entrez:
6
9
2023
Statut:
epublish
Résumé
Researchers performing high-quality systematic reviews search across multiple databases to identify relevant evidence. However, the same publication is often retrieved from several databases. Identifying and removing such duplicates ("deduplication") can be extremely time-consuming, but failure to remove these citations can lead to the wrongful inclusion of duplicate data. Many existing tools are not sensitive enough, lack interoperability with other tools, are not freely accessible, or are difficult to use without programming knowledge. Here, we report the performance of our Automated Systematic Search Deduplicator (ASySD), a novel tool to perform automated deduplication of systematic searches for biomedical reviews. We evaluated ASySD's performance on 5 unseen biomedical systematic search datasets of various sizes (1845-79,880 citations). We compared the performance of ASySD with EndNote's automated deduplication option and with the Systematic Review Assistant Deduplication Module (SRA-DM). ASySD identified more duplicates than either SRA-DM or EndNote, with a sensitivity in different datasets of 0.95 to 0.99. The false-positive rate was comparable to human performance, with a specificity of > 0.99. The tool took less than 1 h to identify and remove duplicates within each dataset. For duplicate removal in biomedical systematic reviews, ASySD is a highly sensitive, reliable, and time-saving tool. It is open source and freely available online as both an R package and a user-friendly web application.
Sections du résumé
BACKGROUND
Researchers performing high-quality systematic reviews search across multiple databases to identify relevant evidence. However, the same publication is often retrieved from several databases. Identifying and removing such duplicates ("deduplication") can be extremely time-consuming, but failure to remove these citations can lead to the wrongful inclusion of duplicate data. Many existing tools are not sensitive enough, lack interoperability with other tools, are not freely accessible, or are difficult to use without programming knowledge. Here, we report the performance of our Automated Systematic Search Deduplicator (ASySD), a novel tool to perform automated deduplication of systematic searches for biomedical reviews.
METHODS
We evaluated ASySD's performance on 5 unseen biomedical systematic search datasets of various sizes (1845-79,880 citations). We compared the performance of ASySD with EndNote's automated deduplication option and with the Systematic Review Assistant Deduplication Module (SRA-DM).
RESULTS
ASySD identified more duplicates than either SRA-DM or EndNote, with a sensitivity in different datasets of 0.95 to 0.99. The false-positive rate was comparable to human performance, with a specificity of > 0.99. The tool took less than 1 h to identify and remove duplicates within each dataset.
CONCLUSIONS
For duplicate removal in biomedical systematic reviews, ASySD is a highly sensitive, reliable, and time-saving tool. It is open source and freely available online as both an R package and a user-friendly web application.
Identifiants
pubmed: 37674179
doi: 10.1186/s12915-023-01686-z
pii: 10.1186/s12915-023-01686-z
pmc: PMC10483700
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
189Informations de copyright
© 2023. BioMed Central Ltd., part of Springer Nature.
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