Lesson 1011 of 2116
AI to Accelerate Meta-Analysis: Screening + Extraction
Meta-analyses take years partly because of screening and extraction tedium. AI handles both at scale — when validated rigorously.
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What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2meta-analysis
- 3systematic review
- 4screening
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Section 1
The premise
Manual screening and extraction limit meta-analysis throughput; AI assistance accelerates both with proper validation.
What AI does well here
- Use AI for first-pass title/abstract screening with explicit accuracy validation
- Use AI for data extraction following pre-specified extraction templates
- Maintain dual-reviewer methodology including AI as one reviewer
- Document AI methodology following PRISMA-AI guidance
What AI cannot do
- Skip the human review entirely — courts of scientific opinion still expect human judgment
- Trust AI on close-call studies for inclusion
- Generate accurate extraction from poorly-structured source papers
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