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leads-literature-mining

leads-literature-mining,来自 FreedomIntelligence/OpenClaw-Medical-Skills 的 agent 技能。

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技能内容

<!--

COPYRIGHT NOTICE

This file is part of the "Universal Biomedical Skills" project.

Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>

All Rights Reserved.

#

This code is proprietary and confidential.

Unauthorized copying of this file, via any medium is strictly prohibited.

#

Provenance: Authenticated by MD BABU MIA

-->


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

<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

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它属于哪个仓库

星标★ 3,010
本站分层T1
该仓技能数897
原文件路径skills/leads-literature-mining/SKILL.md

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