There was an article in the FT last week, commenting on an article in JAMA here. The topic is the use of AI (or, to be fair, other machine learning techniques) to help diagnose skin disease. Google will allow people to upload their own images and will, in turn, provide “guidance” as to what they think it is.
I think the topic important, and I wrote a little editorial on this subject here a few years ago with the strikingly unoriginal title of Software is eating the clinic. For about 8-10 years I used to work in this field but although we managed to get ‘science funding’ from the Wellcome Trust (and a little from elsewhere), and published extensively, we were unable to take it further via commercialisation. As is often the case, when you fail to get funded, you may not know why. My impression was that people did not imagine that there was a viable business model in software in this sort of area (we were looking for funds around 2012-2015). Yes, seemed crazy to me then, too (and yes, I know, Google have not proven there is a business model). Some of the answers via NHS and Scottish funding bodies were along the lines of come back when you prove it works, and then we will then fund the research.?
A few days back somebody interested in digital health asked me what I thought about the recent work. Below is a lightly edited version of my email response.
- Long term automated systems will be used.
- Tumours will be easier than rashes.
- A rate-limiting factor is access to — and keeping — IPR of images.
- The computing necessary is now a commodity and trivial in comparison with images and annotation of images
- Regarding uncommon or odd presentations, computers are much more stupid than humans. Kids can learn what a table is with n<5 examples. Not so for machines. Trying to build databases of the ‘rare’ lesions will take a lot of time. It will only happen cheaply when the whole clinical interface is digital, ideally with automated total body image capture (a bit like a passport photo booth), and with metadata and the diagnosis added automatically.
- In the short term, the Google stuff will increase referrals. They are playing the usual ’no liability accepted, we are Silicon Valley, approach’. They say they are not making a diagnosis, just ‘helping’. This is the same nonsense as 23and me. They offload the follow-up onto medics / health service. Somebody once told me that some of the commercial ‘mole scanners’ sent every patient to their GP to further investigate — and refer on to hospital —their suspicious mole. This is a business model, not a health service.
- Geoffrey Hinton (ex Edinburgh informatics) who is one of the giants in this area of AI says in his talks that ‘nobody should train as a radiologist’. He is right and wrong. Yes, the error rate in modern radiology is very, very high — simply because they are reporting so many ‘slices’ in scans in comparison with old-fashioned single ‘films’ (e.g. chest X-ray). But single bits of tech in medicine are often in addition to what has previously happened rather that a replacement. In this domain, radiologists now do a lot more than just report films. So, you will still need radiologists but what they do will change. Humans are sentient beings and, given the right incentives, doctors are remarkably creative.
- There is still a very narrow perspective on skin disease in the UK, with a continued denial of the necessity for expertise. Primary care dermatology by doctors — let alone nurses who know even less and do not have professional registration in this domain of expertise — is a mess. It requires perceptual skills, and not unreasonably, many GPs do not have this because they have to know so much across a broad area of medicine. The average GP will see 1 melanoma every ten years. I started my dermatology training in Vienna: there are more dermatologists in Vienna than the whole of the UK. Specialism, pace Adam Smith and the pin factory, is what underpins much of the power of capitalism — and medicine, too. (Note: in this regard, some of the comparisons in the JAMA paper are facile).
- I think the machines will play a role and we are better with them than without them. But in the short term, demands on hospital practice will increase and waiting times will increase even further. This technology — in the short to medium term — will make things worse. At present, dermatology waiting times are worse than when I was a medical student (and this was true pre-Covid). You don’t need AI to know why.
If only we had been funded…. ?. Only joking.