AI-powered literature screening tool
Top 39.1% on sourcepulse
MetaScreener is an AI-powered tool designed to significantly accelerate literature screening for systematic reviews and other research projects. It targets researchers and institutions aiming to reduce the time and effort associated with manually reviewing large volumes of academic papers, promising to cut screening time by up to 89%.
How It Works
MetaScreener employs a human-AI partnership model, allowing users to leverage various large language models (OpenAI, Claude, Gemini, DeepSeek) for abstract and full-text analysis. Users define screening criteria based on established research frameworks (e.g., PICOT, SPIDER) and upload documents (RIS, PDFs). The system then processes these, providing reasoned decisions and extracting data, with a strong emphasis on privacy by processing data locally.
Quick Start & Requirements
git clone
, pip install -r requirements.txt
, and python app.py
. OCR for PDFs requires Tesseract.Highlighted Details
Maintenance & Community
Developed by researchers from the University of Oxford and the Oxford University Clinical Research Unit. Active community engagement via GitHub Issues and Discussions. Roadmap includes active learning, a REST API, and multi-user collaboration.
Licensing & Compatibility
The project is marked as "Open Source" but does not specify a license type in the README. This requires clarification for commercial use or linking with closed-source projects.
Limitations & Caveats
The specific open-source license is not clearly stated, which could impact commercial adoption. While it supports multiple LLMs, performance and cost will vary significantly between providers. The tool is primarily focused on English-language literature, with multilingual support planned for the future.
2 months ago
Inactive