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A newer version of the Gradio SDK is available: 5.45.0

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metadata
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.