It has affected a small number of fields for sure. Imaging based diagnosis might be better off due to ML, but imaging based diagnosis isn't going to cure cancer or be helpful for every single disease. Glad it's helping but the authors point is only reinforced. Unless you can make a case that we will cure basically everything with ML that is.
Imaging based diagnosis is not going to cure cancer, but it can guide treatment - based on what the AI reads from the images patients can get drugs that are very effective for their particular cancer. We have very effective drugs nowadays, large part of treating cancer is figuring which drug to give.
Imaging based diagnosis could read presence or absence of particular gene mutations from the images so that the genes can be silenced by the drugs.
Imaging based diagnosis could also figure out whether a particular cancer precursor is going to develop into invasive cancer and do it better than the experts we have now (otherwise we wouldn't use the AI).
This can also be done cheaper than paying consultants to figure it out and it can be done in locations where they don't have the specialists.
Some companies working in the field (some already have tools approved for use on patients):
> Imaging based diagnosis could read presence or absence of particular gene mutations from the images so that the genes can be silenced by the drugs.
>Imaging based diagnosis could also figure out whether a particular cancer precursor is going to develop into invasive cancer and do it better than the experts we have now (otherwise we wouldn't use the AI).
Where is the evidence for these claims, other than a VC hype sheet? Like real clinical trials. These claims also show a fundamental misunderstanding of what this data can tell us. Imaging data doesn't give you tumor genetic profiles. It can give you tumor phenotype, which is associated with specific mutations. To get the true genetic profile you need to do deep sequencing at tens of thousands of dollars per tumor, and even then you have the problem of tumor heterogeneity, which lets the cancer evade the treatment.
A major concern I have working in this space is that we're selling people on grand promises of far off possibilities rather than what we can actually deliver right now.
Just the latest iteration of people who don't know biology (used to be Physicists, now it's the AI guys) coming in to save all of us. Once in a while someone does make meaningful contributions, but in the end it's hard to say if the collective investment in attention and money have made it worthwhile or not.
ML diagnosis could actually be worse for us overall, as we might find more harmless cancers and subject people to more unnecessary tests and treatments. Iatrogenic harms are real, especially when ML gives us only diagnostics, and never any treatments.
