Single file including all html/js/css, Vanilla JS, no backend, scores persisted with localStorage.
Deployed using ubuntu/apache2/python/flask on a £5 Digital Ocean server (but could have been hosted on a static hosting provider as it's just a single page with no backend).
Images / metadata stored in an AWS S3 bucket.
A dermatologist a short while ago with this idea would have to find a willing and able partner to do a bunch of work -- meaning that most likely it would just remain an idea.
This isn't just for non-tech people either -- I have a decades long list of ideas I'd like to work on but simply do not have time for. So now I'm cranking up the ol' AI agents an seeing what I can do about it.
You just need one program that can read the training data, train a model, and then do the classification based on input images from the user.
This works for basically any kind of image, whether it's dogs/cats or skin cancer.
You can take the code from a dog/cat classifier and use it for anything.
You only need to change the training data.
And, more importantly, I don't think you'll see good results either from a vibe-coded solution.
So I don't think your comment makes sense here.
I'm not going to argue with the idea that a pre-made classifier can be improved upon by experts.
But pre-made classifiers exist and are useful for a very large variety of tasks. This was the original point.