BioLitAI: Intelligent Literature Mining and Research Gap Detection Tool

An AI-powered web application for biomedical researchers to automatically search, summarize, and analyze scientific literature to identify research gaps.

Features

• 🔍 Literature Search: Search PubMed for biomedical papers
• 📝 Intelligent Summarization: Auto-summarize papers using Mistral-7B LLM
• 🏷️ Named Entity Recognition: Extract diseases, genes, drugs, methods, and datasets
• 💡 Research Gap Detection: AI-powered analysis to suggest potential research gaps
• 💾 SQLite Database: Store and retrieve research findings
• 🎨 Interactive UI: Streamlit-based user interface

Tech Stack

• Backend: Python
• UI Framework: Streamlit
• NLP Models: Hugging Face Transformers (Mistral-7B), spaCy
• Database: SQLite
• API: PubMed (free public endpoint)

Project Structure

BioLitAI/
├── README.md
├── requirements.txt
├── config.py
├── src/
│   ├── __init__.py
│   ├── pubmed_api.py          # PubMed API wrapper
│   ├── llm_summarizer.py      # LLM-based summarization
│   ├── ner_extractor.py       # Named Entity Recognition
│   ├── gap_detector.py        # Research gap detection
│   └── database.py            # SQLite database operations
├── app.py                      # Streamlit main application
└── data/
    └── bioliteai.db           # SQLite database (auto-created)

Installation

1. Clone the repository

   git clone https://github.com/sufaismail/BioLitAI.git
   cd BioLitAI

2. Create a virtual environment

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies

   pip install -r requirements.txt

4. Download spaCy model

   python -m spacy download en_core_sci_md

Usage

Run the Streamlit app:

streamlit run app.py

Then open your browser to http://localhost:8501

How It Works

1. Search: Enter keywords to search PubMed
2. Analyze: Papers are automatically summarized and analyzed
3. Extract: Diseases, genes, drugs, methods, datasets are extracted
4. Detect Gaps: AI identifies potential research gaps
5. Store: Results are saved to the database for future reference

Features in Development

• Export results to PDF/CSV
• Advanced filtering and sorting
• Collaboration features
• Citation management
• Multi-language support

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License

Author

sufa ismail

Support

For issues, questions, or suggestions, please open an issue on GitHub.