Cargando…
Technology-assisted title and abstract screening for systematic reviews: a retrospective evaluation of the Abstrackr machine learning tool
BACKGROUND: Machine learning tools can expedite systematic review (SR) processes by semi-automating citation screening. Abstrackr semi-automates citation screening by predicting relevant records. We evaluated its performance for four screening projects. METHODS: We used a convenience sample of scree...
Autores principales: | Gates, Allison, Johnson, Cydney, Hartling, Lisa |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5848519/ https://www.ncbi.nlm.nih.gov/pubmed/29530097 http://dx.doi.org/10.1186/s13643-018-0707-8 |
Ejemplares similares
-
The semi-automation of title and abstract screening: a retrospective exploration of ways to leverage Abstrackr’s relevance predictions in systematic and rapid reviews
por: Gates, Allison, et al.
Publicado: (2020) -
Faster title and abstract screening? Evaluating Abstrackr, a semi-automated online screening program for systematic reviewers
por: Rathbone, John, et al.
Publicado: (2015) -
Machine learning for screening prioritization in systematic reviews: comparative performance of Abstrackr and EPPI-Reviewer
por: Tsou, Amy Y., et al.
Publicado: (2020) -
Decoding semi-automated title-abstract screening: findings from a convenience sample of reviews
por: Gates, Allison, et al.
Publicado: (2020) -
Performance and usability of machine learning for screening in systematic reviews: a comparative evaluation of three tools
por: Gates, Allison, et al.
Publicado: (2019)