Earlier quoted context omitted.
For something like optimal diets for everyone, I imagine it's more of an issue with incomplete understanding of diet, microbiome, genetics, epigenetics, etc. Once that's known, I'd venture to say you don't need AI. But a GAN where the discriminator is determining if a joke is made by an AI or a human might be pretty cool :)
> For something like optimal diets for everyone, I imagine it's more of an issue with incomplete understanding of diet, microbiome, genetics, epigenetics, etc. Once that's known, I'd venture to say you don't need AI. Even if the data exists, doesn't mean the AI folks would use it. In my research (a particular subfield of fluid dynamics), the machine learning/AI papers/talks always seem to have incomplete or even bad…
The whole thing is about how to build these fancy networks, and it created a fair bit of buzz. Table S1, in the supplement, however shows that it's rather pointless.
The deep model has an AUC (95% CI) of [0.94, 0.96] for in-patient mortality. The "full feature-enhanced" logistic regression baseline has an AUC of [0.92, 0.95]. Same pattern for 30 remission. Length of stay is the only one that's not overlapping, and it just squeaks that out: [0.86, 0.87] for the deep model vs. [0.84, 0.85] for the baseline.