Project Title: Cancer Information Retrieval from External Data Sources using RAG and Gemini Pro LLM Models

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). :rocket:

In this groundbreaking endeavour, we are harnessing the power of Generative AI and the RAG model, along with the Gemini Pro LLM .

:mag: 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.

:bulb: 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

1 Like

That great. Why not have a simple demo using Streamlit to create a frontend. Just a humble suggestion. I am not very good in Streamlit though. :blush:

1 Like

That would be a fabulous idea , thanks for reviewing this ,also i am thinking to make it as an end to end project , can create a monitoring system to track all relevant information like , model performance , input output token usage , accuracy , truthfulness , groundedness etc , this project also can part of learning procedure to all Gen AI enthus out there.