How I Built a Super-Doctor Using Advanced RAG

The average doctor sees around one hundred thousand patients in their lifetime. In this talk, I’ll show you how you can build a super-doctor capable of retrieving from over 150,000+ unique patient cases and 3M medical publications to answer patient-related questions. I will use advanced retrieval augmented generation(RAG) techniques such as hybrid search, re-ranking, query generation, and semantic text chunking. Combine these with some of the best LLMs around, specialized biomedical embedding models, and scalable vector databases and we can build a medical chatbot with more information than any doctor alive!

About the speaker

Zain Hasan

Senior ML Developer Advocate at Weaviate

Zain Hasan is a senior ML developer advocate at Weaviate, an open-source vector database. An engineer and data scientist by training, he pursued his undergraduate and graduate work at the University of Toronto St. George building artificially intelligent assistive technologies, then founded his company, VinciLabs, which operated at the intersection of digital health and machine learning. More recently he practiced as a consultant senior data scientist in Toronto. Zain is passionate about the field of machine learning, education, and public speaking.




Sessions: April 2nd – 3rd 2024
Trainings: April 15th – 19th 2024



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