The first thing I’d say, and this is really important: You need to put a disclaimer on the site clearly stating that it’s not medical advice of any kind.

Explainability is always the sticking point in healthcare. This is pretty cool, but unless you can explicitly state why the model is giving that advice/output, it can never be truly useful, and worse, can open you up to all sorts of issues around accountability and liability. Tracing back to the original studies is a good thing, but doesn’t necessarily answer the question of why the model thinks that study should result in that advice.

Deep Learning models in healthcare are typically relegated to the realms of decision-support at best for the moment because of these issues. Even then, they’re often ignored by clinicians on the whole for a variety of reasons.

The methodology for determining what advice to give is quite shaky too. There is usually a bit more to answering these kinds of questions. What are the effect sizes given in the studies, for example? What kind of studies are they?

Anyway, I hope that doesn’t come across as overly-critical and is constructive in some way. AI/ML for healthcare can be a bit of a minefield, but it’s my area of research so just thought I’d pass on my thoughts.

Edit just to add: It would probably be really beneficial for you to talk to a clinician or even a med student about your project. From my experience, it's pretty much impossible to build effective tools or produce good, impactful research in this domain without input from actual clinicians.