leads-literature-mining

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Review Automator

mdbabumiamssm By mdbabumiamssm schedule Updated 2/10/2026

name: leads-literature-mining description: Review Automator keywords: - literature-mining - systematic-review - meta-analysis - pubmed - evidence-synthesis measurable_outcome: Complete a systematic review screen of 100+ papers with >90% inclusion/exclusion accuracy compared to human baseline. license: CC-BY-4.0 metadata: author: Nature Communications 2025 version: "1.0.0" compatibility: - system: Python 3.9+ allowed-tools: - run_shell_command - web_fetch

LEADS (Literature Mining Agent)

A specialized LLM agent for automating systematic reviews and meta-analyses, capable of high-accuracy study selection and data extraction.

When to Use

  • Systematic Reviews: Screening thousands of abstracts for inclusion criteria.
  • Data Extraction: Pulling specific metrics (e.g., hazard ratios, sample sizes) from full-text PDFs.
  • Evidence Synthesis: Aggregating findings across multiple studies.

Core Capabilities

  1. Study Selection: Automated screening based on PICO criteria.
  2. Data Extraction: Structured extraction of study characteristics and results.
  3. Quality Assessment: Risk of bias evaluation.

Workflow

  1. Search: Query PubMed/Embase.
  2. Screen: Apply inclusion/exclusion criteria to abstracts.
  3. Extract: Parse full text for data points.
  4. Report: Generate PRISMA flow diagram and evidence table.

Example Usage

User: "Perform a systematic review on the efficacy of CAR-T in solid tumors."

Agent Action:

python -m leads.review --topic "CAR-T solid tumors" --criteria ./criteria.json
Install via CLI
npx skills add https://github.com/mdbabumiamssm/LLMs-Universal-Life-Science-and-Clinical-Skills- --skill leads-literature-mining
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