Medical AI has a bit of an accessibility problem.

On one side: research papers, specialist tooling, regulatory acronyms, and models with names that sound like rejected Pokemon.

On the other: people pasting their entire medical history into ChatGPT and hoping for the best.

There is quite a lot in between.

In this talk, we’ll take a hands-on tour through the surprisingly large zoo of open and freely available AI models for medical information. We’ll look at what kinds of models are out there, what they are actually useful for, and how developers, researchers, and curious patients can experiment with them without first joining a hospital research lab.

We’ll segment medical images, fine-tune imaging models, search and chat with medical information using specialized embeddings, and combine text, images, and structured data into multimodal workflows.

Some of these models are surprisingly capable. Some are oddly specific. Some come with three citations, a GitHub repo, and absolutely no instructions.

By the end, you should have a much better map of this strange little corner of AI: what you can build today, where the sharp edges are, and where to start if you want to play with medical AI yourself.