Lesson 104 of 2244
AI-Driven Systematic Reviews: The New Workflow
Tools like Elicit and ASReview are reshaping systematic review. Here's how to use them without sacrificing rigor.
Adults & Professionals · Research & Analysis · ~24 min read · Interactive
What AI tools actually do in systematic review
Compare the options
| Tool | Strength | Best used for |
|---|---|---|
| Elicit | Natural-language question to paper list with extraction | First pass on a new question |
| ASReview | Active-learning screening against criteria | Title/abstract screening at scale |
| Rayyan | Collaborative screening | Multi-reviewer teams |
| Consensus | Claim-level search across papers | Answering 'what does the literature say about X?' |
| Covidence | End-to-end systematic review management | PRISMA-compliant reviews |
The hybrid workflow that works
- 1Formulate PICO question (Population, Intervention, Comparator, Outcome)
- 2Build search strings the traditional way in PubMed / Scopus / Web of Science
- 3Import results into Rayyan or ASReview
- 4Train the AI screener on your first 100-200 decisions
- 5Let AI rank remaining abstracts; human-review top-ranked until stopping criteria
- 6Full-text screen human-first; AI flags concerns
- 7Extract data with Elicit-style tools, human-verify every row
- 8Report AI-assistance methods per PRISMA-AI guidance
💡 Try it yourself
Open an AI assistant (Claude, ChatGPT, or Gemini) and practice what you just learned.
→ Apply the concept from this section in a real prompt
→ Note what worked and what surprised you
Key terms in this lesson
The big idea: AI systematic-review tools are not shortcuts — they are force multipliers for a rigorous workflow. Rigor first, speed second.
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