Plenty of people (including myself) in biomedical fields (especially in bioinformatics, although I know of numerous medically-oriented users) use RDF for a variety of purposes- it's a fabulously flexible way to express and encode complex data models. With a little bit of coordination regarding semantics (OWL, etc.), it's also a great way for people in related but distinct fields to share their data with one another.

That said, RDF has historically had three main problems, IMHO. The first is that its proponents have, historically speaking, done a crappy job of explaining what it actually is, and a worse job of demonstrating what it can do.

The second problem is that it's not really the most human-readable format around, especially in its XML serialization format. This is largely because it wasn't designed for human-readability, but in the age of the Web (where human-readable formats have shown to have major advantages over non-human-readable ones), this is a liability. They've added some more readable serialization formats over the years, but a lot of the documentation and tutorials assume that you'll be working in XML.

When I first tried to learn about RDF, years ago, all I found were tutorials full of really gnarly-looking XML with minimal explanation of what was going on. I spent so much time getting bogged down by the syntax that I missed the point entirely.

The third, and bigger, problem with RDF, is that it's a little hard to "grok" if you don't have a good grounding in predicate logic, description logics, and some of its other theoretical underpinnings. Actually, wait, maybe I said that wrong- I should say instead that most of the old-school RDF people do have solid theoretical backgrounds in description and predicate logic, and have a hard time talking about RDF and other semweb technologies with people who people who don't have that background. So they use lots of jargon that, while useful, isn't very helpful to somebody just trying to get their feet wet.