ChaokunHong/MetaScreener

Health v2 · maintenance only

Adoption not part of the score

1328 stars · 49 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

MetaScreener is an open-source AI tool that automates title/abstract and full-text PDF screening for systematic reviews using an ensemble of multiple open-source LLMs with calibrated confidence scoring. It ingests RIS/BibTeX/CSV search results, applies PICO/PEO/SPIDER criteria, auto-decides high-confidence cases, and routes uncertain ones to human review with full audit trails.

Use cases

• screen abstracts for a systematic review with AI
• automate title and abstract screening of PubMed search results
• apply PICO inclusion criteria to thousands of papers
• screen full-text PDFs with OCR for a meta-analysis
• reduce manual literature screening time in evidence synthesis
• flag uncertain studies for human review during screening
• export screening decisions to RIS or CSV for a review manager

When to choose

• you are conducting a systematic review or meta-analysis and need to screen large volumes of citations
• you want reproducible, auditable AI screening with confidence scores rather than a single black-box model
• you need human-in-the-loop triage where only uncertain cases reach a reviewer
• you want a low-cost, privacy-conscious option using open-source LLMs and your own API keys

When to avoid

• you need fully automated screening with no human verification, as the tool is designed to escalate uncertain cases
• your review requires strict journal or Cochrane compliance that prohibits LLM-assisted screening
• you lack API access to any of the supported LLM providers
• you need a simple single-model classifier rather than a multi-LLM ensemble pipeline

Facets

application · maturity active

llm-inference rag ocr pdf machine-learning web-framework api-framework healthcare large-language-models artificial-intelligence education data-science python self-hosted cross-platform cli systematic-review literature-screening meta-analysis evidence-synthesis multi-llm-ensemble pico-criteria human-in-the-loop confidence-calibration active-learning ris-import natural-language-processing docker web-server

Member repositories

For agents

markdown · JSON · MCP: product_card(name="ChaokunHong/MetaScreener")