AI in healthcare feels like something that is constantly talked about at the moment
and what I found kind of an interesting learning experience is trying to
separate the hype from the reality this is the definition that's used in the
government's industrial strategy, so they define AI as technologies with the
ability to perform tasks that would otherwise require human intelligence
such as visual perception speech recognition and language translation so
for example machine learning which is something that a lot of the conversation
focuses around and it's about how you essentially build an artificial neural
network so it's inspired by how the brain works where you can train it to
analyse information by training it on different data sets. Natural language
processing is another thing that is often talked about so for example
analysing speech of a doctor and converting that into text. Image
recognition is really important for the medical imaging and pathology and then
chatbots and things like that. How is AI use in healthcare? There are
kind of five broad types so the first category being process optimisation
which is things like logistics and procurement and HR. Preclinical research
so from a broad Cancer Research UK perspective this is something we're
quite interested in exploring so for example in drug discovery
crunching huge amounts of genomic data. Clinical pathways which is for example
using AI in parts of diagnostics or understanding a patient's prognosis it's
things like you know using AI to analyse a breast screening image for example and
then patient-facing applications which I think really fascinating so chatbots
personalised health advice using wearables. Population-level applications
so this is about you know big data sets and analysing larger trends. In terms of
what I've come across the most progress has been made in image related tasks in
clinical pathways so radiology and pathology being the two main ones. What's
really important to say up front is that I think there is a lot of hype out there
and a lot of bold claims made about you know we won't need radiologists in the
future the kids will just plug it into an AI.
The consensus I seem to have heard so far is it seems to be more about
augmenting tasks or automating part of someone's workflow rather than wholesale
replacing people. I think there's been a lot of attention given to using AI to
determine you know much broader parts of patient pathways while I think
everyone's arguably you know very excited about this and none of this stuff is
really really immediate. The other thing just to be aware of is there a is to
some extent already pretty well embedded in clinical pathways so aspects already
of radiotherapy that's fully automated and is AI-based but that's just kind of
how it's worked it's not been a big hype thing like there has been for imaging
it's just been a kind of natural progression of the software. In the
screening space breast radiology is a really interesting area and there's some
large-scale trials going on at the moment which are really exciting where
it is more applicable is to tasks which are binary which are repetitive and
which are underpinned by large data sets so screening is a pretty obvious example
of that you know huge data sets. To realise potential there are a few things
we need. This relies on really consistently high quality data so you
know you have to have good quality data for the decision made by AI to be
trustworthy and while cancer data is often heralded even when we do what
seemed to be relatively basic analysis of treatment data there's a huge amount
of cleaning that has to go into that. Interoperability is
also really important so one of the screening test beds at the moment,
they all have consortium with all the IT, they've all got the same IT system
they've got a joint agreement and that's why it's working well but that's not the
case for the rest of the country. Frameworks for adoption in diffusion so
do we have the right regulatory pathway for AI? Do we have the right ways of
getting from a test bed to nationwide equitable access? Not at the moment.
Do we have a system that works for patients? How do we build that? Also workforce
so The Topal Review which was out recently says that within 20 years 90%
of all jobs in the NHS will require some element of digital skills but to get to
the point where 90% of staff in the NHS feel comfortable using this
stuff there needs to be a lot of training
throughout that including ethics. In summary AI definitely won't replace all
doctors and it definitely won't replace the value of a good doctor-patient
relationship and treatment decision-making discussion but it could have huge
potential in improving patient care, improving patient experience and inefficiency savings as well