ML for healthcare. The whole industry is so far behind everything else, it is not even funny. Problem is, Just like Airbnb or Uber, the biggest road blocks are not technological, they are organizational and political. It is entirely possible, we might need some major privacy / security related leaps in ML to convince the medical industry to adopt it fully. ML in movies and rendering. Deep Fakes is just an amateur's t…
> ML for healthcare. I'm kind of apprehensive about this advancement. There's many ways to mess this up, from intentional dataset poisoning (to encourage patients to get unnecessary procedure) to just terrible errors made with just a shift in data capture methodology. This paper has a lot of detail on how such systems can fail ( https://arxiv.org/pdf/1804.05296.pdf ).
Within the current system- you can just skip to encouraging patients to get unnecessary procedures. At worst, ML adds an extra step.
It's important to remember that innovation doesn't have to be perfect, it just has to be better than the system it replaces.