Article type
Year
Abstract
Objectives: To provide an opportunity to experience the full customizability, ease of use and intuitive interface of Rayyan (rayyan.qcri.org).
Enabling evidence-based health care will depend on the availability of high-quality, up-to-date clinical resources. Disseminating these resources in a timely fashion requires efficient sharing, evaluation, and analysis of all relevant primary research and ultimately its distillation into SRs. Rayyan provides an end-to-end platform for automating the creation of systematic reviews, making the process faster and more accurate. Rayyan enables rapid citation screening via online contemporaneous sharing of decisions by reviewers, significantly reducing the time required to complete preliminary filtering of searches. It permits individualized labelling of reviewers’ agreements/disagreements against inclusion criteria and provides real-time automatic suggestions for studies to be considered for inclusion using an efficient machine-learning algorithm. Risk of bias analysis and dat extraction from full texts are additional features.
Description: Participants will learn to create reviews, invite collaborators, upload citations, manage duplicates, use facets, e.g. word cloud, keywords for exclusion/inclusion, and authors, to navigate through the citations, exclude/include studies, understand Rayyan’s suggestions, navigate the studies using the similarity graph, and upload full text PDFs. Bring laptops, tablets or smart phones for more fun.
Enabling evidence-based health care will depend on the availability of high-quality, up-to-date clinical resources. Disseminating these resources in a timely fashion requires efficient sharing, evaluation, and analysis of all relevant primary research and ultimately its distillation into SRs. Rayyan provides an end-to-end platform for automating the creation of systematic reviews, making the process faster and more accurate. Rayyan enables rapid citation screening via online contemporaneous sharing of decisions by reviewers, significantly reducing the time required to complete preliminary filtering of searches. It permits individualized labelling of reviewers’ agreements/disagreements against inclusion criteria and provides real-time automatic suggestions for studies to be considered for inclusion using an efficient machine-learning algorithm. Risk of bias analysis and dat extraction from full texts are additional features.
Description: Participants will learn to create reviews, invite collaborators, upload citations, manage duplicates, use facets, e.g. word cloud, keywords for exclusion/inclusion, and authors, to navigate through the citations, exclude/include studies, understand Rayyan’s suggestions, navigate the studies using the similarity graph, and upload full text PDFs. Bring laptops, tablets or smart phones for more fun.