Thrilled to unveil my latest project - “Cancer Information Retrieval from External Data Sources using RAG(Retrieval Augmented Generation) and Google Gemini Pro Models” - a project at the forefront of innovation, to revolutionize cancer information retrieval and understanding, spanning various types including :
→ Cervical Cancer
->Breast Cancer
->Oral Cancer
->Ovarian Cancer and more.
using LangChain and Pinecone (Vector DB).
In this groundbreaking endeavour, we are harnessing the power of Generative AI and the RAG model, along with the Gemini Pro LLM .
Key Features:
- Data Extraction: Collecting insights from diverse sources, including HTML and PDF documents.
- Information Synthesis: Utilizing RAG to distill extracted data into concise and accurate summaries.
- Question Answering: Empowering users to find answers to specific queries directly and factually.
Benefits:
→ Comprehensive Access: Offering a holistic view by gathering information from various sources.
→ Efficient Processing: Streamlining information extraction and summarization for time-saving and initial idea before doctor consultation.
→ Improved Accessibility: Presenting complex data in clear, concise, and user-friendly formats.
→ Enhanced Engagement: Encouraging user interaction and deeper learning through creative text generation.
Let’s innovate for a healthier future!
more details : GitHub - Ashis-Palai/Cancer_Information_RAG_GenAI