Shirli Di-Castro Shashua

In the ever-evolving landscape of healthcare, doctors face an ongoing challenge: how to swiftly access vital medical information about their patients buried deep within databases. Traditional methods have proven time-consuming and often fall short of providing the comprehensive answers doctors need. But, what if I told you that AI, SQL, and GraphQL have walked into fertility clinics, offering a groundbreaking solution?

In my presentation, I explore the innovative use of Large Language Models (LLMs) in medical feature development. I delve into a novel approach that leverages LLMs to translate doctors’ intricate questions into SQL and GraphQL queries, enabling prompt and accurate retrieval of patient data. The result? A revolution in the way doctors access and utilize critical information to make informed decisions.

Join me at the development table as we uncover the objectives behind crafting the “”chatting with my medical database”” feature. Together, we’ll unravel how LLMs became integral to this feature, and how GraphQL emerged as the superhero, leaving SQL in the dust. We will delve deep into the key development considerations that influenced our choices, encompassing security, flexibility to handle diverse inputs, and reliability in providing doctors with answers to their questions.