Performance and usability of machine learning for screening in systematic reviews: a comparative evaluation of three tools

BACKGROUND: We explored the performance of three machine learning tools designed to facilitate title and abstract screening in systematic reviews (SRs) when used to (a) eliminate irrelevant records (automated simulation) and (b) complement the work of a single reviewer (semi-automated simulation). W...

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Detalles Bibliográficos
Autores principales: Gates, Allison, Guitard, Samantha, Pillay, Jennifer, Elliott, Sarah A., Dyson, Michele P., Newton, Amanda S., Hartling, Lisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6857345/
https://www.ncbi.nlm.nih.gov/pubmed/31727150
http://dx.doi.org/10.1186/s13643-019-1222-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6857345/
https://www.ncbi.nlm.nih.gov/pubmed/31727150
http://dx.doi.org/10.1186/s13643-019-1222-2

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