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---
title: "GLiNER-BioMed PICO Extractor"
emoji: 🧠
colorFrom: gray
colorTo: blue
sdk: gradio
sdk_version: "4.0.0"
app_file: app.py
pinned: false
---
# GLiNER-BioMed PICO Extractor
This Hugging Face Space extracts PICO elements (Population, Intervention, Comparison, Outcome) from:
- Raw biomedical abstracts
- `.nbib` reference files
### Model
Powered by `Ihor/gliner-biomed-bi-small-v1.0` — a compact BERT-like NER model trained for biomedical text using synthetic annotations.
### Features
- ✅ Zero-shot extraction using natural language entity descriptions
- 📄 NBIB parser for PubMed export files
- ⚡ Lightweight: deploys on CPU-only Spaces
### How to Use
1. **Paste a biomedical abstract** in the textbox → Get labeled PICO entities.
2. **Upload a `.nbib` file** → Get per-abstract PICO extractions.
### Dependencies
- `gradio`
- `gliner`
- `torch`
- `transformers`
---
Inspired by the needs of evidence-based medicine and large-scale systematic reviews.
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