I am a medical oncologist in a similar position to you. I agree completely. There is a lot of hype over 'AI' and big data, and plainly ridiculous statements abo

I am a medical oncologist in a similar position to you. I agree completely. There is a lot of hype over 'AI' and big data, and plainly ridiculous statements about replacing doctors etc. The technology is fascinating, and there has been a lot of interesting and clever innovations. But the value add for healthcare is pretty small in the end. The value add for the actual patient is even more miniscule. There is some misunderstanding about what doctors actually do and what patients want doctors to do. Fundamentally, a patient wants to see a doctor that is going to take responsibility for their medical problem, and ideally their health. When this is achieved, the outcomes are usually optimal under constraints, and the clinician and patient are both satisfied. 'AI' as it is known today could never do this. Even if someone unveils superhuman general AI tomorrow, it wouldn't be able to do this. There are various niche applications of machine learning which employ interesting technology in image interpretation, and this will be a useful addition to the suite of tools already present, particularly where non-specialists need to look at a picture or radiological image, and for screening. But otherwise I expect that in 20 years time we will still be saying that EMR data is too difficult to deal with, and uptake of machine learning based software will be very low. We still don't have useful automated reporting of electrocardiograms, for example. So even sophisticated curve fitting seems to have trouble fitting these literal curves in a way that impacts clinical care.