Speed up abstract screeningwithout losing control.

Most delays happen at title/abstract screening: not at writing. A broad PubMed search can return thousands of references. Manual dual screening at 1-2 abstracts per minute means weeks of work before you even open a full text.

If you searched "too many results in my search systematic review," the bottleneck is usually volume plus duplicate records from multiple databases: not lack of effort.

• •Overlapping database exports inflate your library before screening starts.
• •Dual independent review doubles the human hours required.
• •Maybe decisions and conflict resolution add another pass through the pile.

Before any AI or manual screening, collapse duplicate records from PubMed, Embase, Cochrane, and grey-literature exports. Deduplication alone often removes 15-30% of rows: instant time saved with no accuracy trade-off.

Meta-analysis360 imports RIS, BibTeX, NBIB, and EndNote formats, then deduplicates before screening so your team never reads the same abstract twice.

For large libraries, fully manual screening is the slowest defensible step. Generative AI acts as an additional reviewer, using your calibrated eligibility criteria to suggest Include, Exclude, or Maybe on each title/abstract. You get a specific rationale you can easily verify, achieving 99%+ recall when combined with human expertise.

You apply or override every suggestion. The AI is a dedicated co-researcher that never gets tired. You remain the decision-maker for PRISMA reporting and publication, ensuring zero eligible studies are lost.

• •Sort by AI suggestion to clear obvious excludes first.
• •Use keyword highlights to spot PICO terms quickly.
• •Run blind dual review where your team policy requires it.

Accelerated screening only works if accuracy stays high. Keep human confirmation on every final label, spot-check AI includes against your protocol, and resolve team conflicts the same way you would in Covidence or Rayyan. This 100% reproducible workflow creates a full audit trail.

The goal is not to remove reviewers: it is to remove the repetitive first pass through obvious irrelevant abstracts so your time goes to borderline cases and full-text review.