Your Biomedical Knowledge Assistant 🧬📚

InsightMed is a powerful, AI-driven tool designed to simplify and accelerate the exploration of scientific articles in the biomedical domain. Whether you're navigating complex literature on topics like MET (Mesenchymal-Epithelial Transition) or analyzing treatment trends, this solution provides a streamlined interface to interact with, summarize, and visualize insights from scientific research.

Features 🚀

1. Chat with Your Article 🗨️

   Engage in a conversation with individual research articles. Simply upload a PDF, ask questions, and receive contextually accurate answers based on the content of the article.

   • Configure options such as the number of chunks to retrieve, the search method, and the generation model.
   • Designed to save hours of manual reading and comprehension.

   

2. Summarize Your Article ✍️

   Get concise, structured summaries of any uploaded article.

   • Upload the PDF and let the tool extract key insights and generate a summary.
   • Perfect for quickly understanding research without reading every detail.

3. Treatment Visualization Dashboard 📊

   Gain a broader perspective by visualizing data extracted from multiple articles.

   • View trends and features such as treatment mentions, types of cancers addressed, article classifications (e.g., research vs. clinical review), and publication dates.
   • Perform sentiment analysis to identify the most promising treatments based on authors' tones.
   • Color-coded and interactive graphs highlight key insights.

   

Getting Started 💻

Prerequisites

• Python 3.10+

Installation

1. Clone this repository:

   git clone https://github.com/your-repo/biomedical-knowledge-assistant.git
   cd biomedical-knowledge-assistant

2. Install dependencies:

   pip install -r requirements.txt

3. Add your OpenAI API key to the .env file:

   touch .env
   echo "OPENAI_API_KEY=your-api-key" > .env

Running the Application

1. Start the FastAPI backend:

   fastapi run src/main_fastapi.py

2. Start the Streamlit front-end:

   streamlit run front/Welcome.py

3. Access the application:

   • API: http://localhost:8000/docs
   • Web App: http://localhost:8501

Technologies Used 🛠️

• FastAPI: Backend API framework for efficient deployment.
• Streamlit: Front-end interface for user interaction.
• LangChain: Framework for handling document retrieval and LLM-based generation.
• OpenAI GPT: Language model for summarization, Q&A, and sentiment analysis.
• Pandas & Matplotlib: Data extraction and visualization.

Contributing 🤝

We welcome contributions to improve this project! Feel free to:

• Submit issues or feature requests.
• Fork the repo and create pull requests.

Acknowledgments 💡

Thank you for using the Biomedical Knowledge Assistant! If you have any ideas or feedback, don't hesitate to share them. Together, we can make scientific knowledge more accessible to everyone.

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Developed with ❤️ for advancing biomedical research understanding