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