Rayyan

Rayyan is a cloud-based web and mobile research platform designed to help researchers screen, organize, and collaborate on systematic and scoping reviews. It supports literature screening and evidence synthesis across different stages of a review. Rayyan helps researchers import references, remove duplicates, screen studies, resolve conflicts, and organize review decisions. Its AI and machine learning features can also help prioritize relevant studies during screening.

How Rayyan Works

Rayyan combines reference management, screening, collaboration, and AI-assisted prioritization in one research workspace.

• Import References: Upload search results from databases such as PubMed, Embase, or Web of Science using RIS, NBIB, or BibTeX files.
• Remove Duplicates: Rayyan identifies duplicate records from different database imports. Researchers can review and resolve duplicates manually or use available auto-resolution tools.
• Screen Studies: Reviewers independently examine titles and abstracts and mark studies as Include, Exclude, or Maybe. Blind screening keeps reviewers from seeing each other's decisions until the review is unblinded.
• Use AI Predictions: As researchers screen studies, Rayyan's machine learning system learns their preferences and gives unread articles star ratings of up to five stars based on predicted relevance.
• Resolve and Export: Teams can resolve conflicting decisions, record exclusion reasons, and export review datasets or PRISMA flow reports.

How We Rated Rayyan

We evaluated Rayyan based on its study screening capabilities, AI assistance, collaboration tools, duplicate detection, mobile accessibility, and overall usefulness for systematic and scoping reviews. We also considered how easily researchers can manage large collections of references and resolve screening decisions. AI predictions should still be reviewed by researchers to maintain accuracy and avoid missing relevant studies.