Research Screener is web software that uses machine learning to help teams find relevant research during systematic reviews. It ranks abstracts so the most relevant appear first, then lets users upload potentially relevant records from a reference tool, flag items as relevant, and add individual notes. A team review area supports clarifying questions and differences during screening. Screening data and results can be exported, including EndNote XML. The service lists support for up to five collaborators and 30,000 abstracts per project, with one year to start a project. Its site says the algorithm has been validated on numerous systematic and scoping reviews and may save up to 96% of abstract-screening time. A free demo is available, but there is no free plan. Paid access is billed once per project: 250.00 AUD for 1 to 5 projects, 200.00 AUD for 6 to 10, and 150.00 AUD for 10 or more. Institutional licensing is available by contacting the maker.
Who it is for
Research Screener suits systematic-review teams that need machine-ranked abstracts, collaborative screening, notes, and exports. The listed project limits fit groups of up to five collaborators handling up to 30,000 abstracts.
What is good
- Machine learning ranks relevant abstracts first
- Team review supports questions and differences
- Exports include EndNote XML
- Up to five collaborators per project
- Free demo available
What to know first
- No free plan
- Maximum 30,000 abstracts per project
- Maximum five collaborators per project
- Projects must start within one year
Verdict
Research Screener organizes abstract screening around machine ranking and team review, with export support for resulting data. Its per-project pricing and stated collaborator and abstract limits should be considered before purchase.
Research Screener plans and pricing
All plansCompared on AI literature review software
- Free plan
- No
- Screening workflow
- Yes
- Systematic review support
- Yes
- Collaboration seats
- 5
- Export formats
- EndNote XML
