Contribution · Application — Research
AI for Literature and Systematic Review
A systematic review traditionally takes 12-18 months and a team of five. LLMs can compress the abstract-screening and data-extraction phases to weeks — but systematic review methodology is rigorous for a reason. The Cochrane and PRISMA frameworks exist because unreviewed literature synthesis misinforms clinical practice and policy. LLMs accelerate; humans adjudicate; the published review is signed by humans accountable for its conclusions.
Application facts
- Domain
- Research
- Subdomain
- Evidence synthesis
- Example stack
- Claude Opus 4.7 for abstract screening and data extraction · Rayyan / Covidence for systematic review workflow · LlamaIndex over PubMed, Scopus, Embase, CENTRAL · Pydantic schemas for PICO extraction · Dual-review reconciliation UI
Data & infrastructure needs
- Literature corpora (PubMed, Cochrane CENTRAL, Scopus)
- PICO / inclusion-exclusion criteria
- Risk-of-bias tools (Cochrane RoB 2, ROBINS-I)
- Prior review protocols
Risks & considerations
- Missing relevant studies — LLM false negatives on screening
- Extraction errors for numerical data (OR, HR, CI)
- Publication bias amplification
- Hallucinated citations — every reference must be verified
- Methodological drift from accepted frameworks (Cochrane, PRISMA)
Frequently asked questions
Is AI for systematic review safe?
With dual-LLM + human adjudication at each step: yes, and it materially speeds up what is otherwise a year-long process. Follow PRISMA 2020 and disclose AI use in your methods section. Human reviewers sign; AI assists.
What LLM is best?
Claude Opus 4.7 with long context handles full-text extraction better than short-context models. Pair with deterministic tools for numerical extraction (meta-analysis data). Never trust the LLM alone on numbers — always verify.
Regulatory concerns?
Research ethics (ICMR, IRB) for the underlying research. Journal disclosure policies (ICMJE) require AI disclosure. Copyright: full-text access rights. DPDPA/HIPAA if individual patient data is involved.
Sources
- PRISMA 2020 — accessed 2026-04-20
- Cochrane Handbook — accessed 2026-04-20
- ICMJE — accessed 2026-04-20