Statistical stopping criteria for automated screening in systematic reviews

Active learning for systematic review screening promises to reduce the human effort required to identify relevant documents for a systematic review. Machines and humans work together, with humans providing training data, and the machine optimising the documents that the humans screen. This enables t...

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Detalles Bibliográficos
Autores principales: Callaghan, Max W, Müller-Hansen, Finn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7700715/
https://www.ncbi.nlm.nih.gov/pubmed/33248464
http://dx.doi.org/10.1186/s13643-020-01521-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7700715/
https://www.ncbi.nlm.nih.gov/pubmed/33248464
http://dx.doi.org/10.1186/s13643-020-01521-4

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