I've read the article :), the author is the same physician who wrote "emperor of all maladies", a book about cancer.
Basically what it comes down to is that doctors get really good at bayesian inference at some point in their career, definitely not while we are students. I am however confident that we can build models that learn in a similar manner.
I'm actually trying to build a model for a class project that uses bayesian inference in a CNN as per Gal et al (https://arxiv.org/abs/1506.02158) to try and detect diabetic retinopathy. Their paper actually tries to detect different skin cancers.
Miiskin tries to develop such a recognition algorithm [0]. To get the training sets they offer a app which allows you to take pictures, periodically reminds you and keep track of moles. The pictures are uploaded outside EU and linked with PII like email, sex & year of birth. Including possible pictures of your face, breasts and genitals [1].
I don't want to pay with my personal data. Is such an app recommended and are there open source alternatives?
I'm not sure that the app is "recommended" per say, but I guess it wouldn't hurt to be extra cautious if you're out in the sun a lot or predisposed.
The only other app I know is SkinIO, developed by some northwestern students if I recall correctly. I'm not certain how it all works, but maybe look into that?
Sounds like a really good match for ML - as long as all the input the physician is detecting is visuals. There could be e.g. a smell or temperature component as well, but it's likely visual is enough to get very high accuracy eventually.
Basically what it comes down to is that doctors get really good at bayesian inference at some point in their career, definitely not while we are students. I am however confident that we can build models that learn in a similar manner.
I'm actually trying to build a model for a class project that uses bayesian inference in a CNN as per Gal et al (https://arxiv.org/abs/1506.02158) to try and detect diabetic retinopathy. Their paper actually tries to detect different skin cancers.