TY - UNPB
T1 - The Automated Systematic Search Deduplicator (ASySD)
T2 - a rapid, open-source, interoperable tool to remove duplicate citations in biomedical systematic reviews
AU - Hair, Kaitlyn
AU - Bahor, Zsanett
AU - Macleod, Malcolm
AU - Liao, Jing
AU - Sena, Emily S.
PY - 2021/5/4
Y1 - 2021/5/4
N2 - Background Researchers who perform systematic searches across multiple databases often identify duplicate publications. Identifying such duplicates (“deduplication”) can be extremely time-consuming, but failure to remove these citations can, in the worst instance, 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 (1,845 – 79,880 citations), which had been deduplicated by human reviewers. We compared the performance of ASySD with Endnote’s automated deduplication option and with the Systematic Review Accelerator 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 0.94-0.99. The tool took less than 1 hour to deduplicate all datasets.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.Competing Interest StatementThe authors have declared no competing interest.
AB - Background Researchers who perform systematic searches across multiple databases often identify duplicate publications. Identifying such duplicates (“deduplication”) can be extremely time-consuming, but failure to remove these citations can, in the worst instance, 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 (1,845 – 79,880 citations), which had been deduplicated by human reviewers. We compared the performance of ASySD with Endnote’s automated deduplication option and with the Systematic Review Accelerator 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 0.94-0.99. The tool took less than 1 hour to deduplicate all datasets.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.Competing Interest StatementThe authors have declared no competing interest.
UR - https://doi.org/10.1101/2021.05.04.442412
U2 - 10.1101/2021.05.04.442412
DO - 10.1101/2021.05.04.442412
M3 - Preprint
BT - The Automated Systematic Search Deduplicator (ASySD)
PB - bioRxiv
ER -