Outcome-based Evaluation of Systematic Review Automation

Author:

Kusa Wojciech1ORCID,Zuccon Guido2ORCID,Knoth Petr3ORCID,Hanbury Allan1ORCID

Affiliation:

1. TU Wien, Vienna, Austria

2. The University of Queensland, Brisbane, QLD, Australia

3. The Open University, Milton Keynes, United Kingdom

Funder

European Commission

Australian Research Council

Publisher

ACM

Reference41 articles.

1. Alexandra Bannach-Brown , Piotr Przybyła , James Thomas , Andrew S. C. Rice , Sophia Ananiadou , Jing Liao , and Malcolm Robert Macleod . 2019. Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error. Systematic Reviews 2019 8:1 , Vol. 8 , 1 (1 2019 ), 1--12. https://doi.org/10.1186/S13643-019-0942--7 10.1186/S13643-019-0942--7 Alexandra Bannach-Brown, Piotr Przybyła, James Thomas, Andrew S. C. Rice, Sophia Ananiadou, Jing Liao, and Malcolm Robert Macleod. 2019. Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error. Systematic Reviews 2019 8:1, Vol. 8, 1 (1 2019), 1--12. https://doi.org/10.1186/S13643-019-0942--7

2. On the use of systematic reviews to inform environmental policies

3. The APISSER Methodology for Systematic Literature Reviews in Engineering

4. Aaron M Cohen , Kyle Ambert , and Marian McDonagh . 2010. A prospective evaluation of an automated classification system to support evidence-based medicine and systematic review . In AMIA annual symposium proceedings , Vol. 2010 . American Medical Informatics Association , 121. Aaron M Cohen, Kyle Ambert, and Marian McDonagh. 2010. A prospective evaluation of an automated classification system to support evidence-based medicine and systematic review. In AMIA annual symposium proceedings, Vol. 2010. American Medical Informatics Association, 121.

5. Reducing Workload in Systematic Review Preparation Using Automated Citation Classification

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