AI in medicine: Friend or foe?
BY Helen Cowan
18th Oct 2023 Health
3 min read
Is AI in medicine a good
idea or bad, is it ethical and will it improve or damage the doctor-patient
relationship?
Whether
helping you search the web, recommending content on Netflix or products on Amazon,
or immortalising Abba as a virtual version of themselves in digital,
life-size avatars—or “ABBAtars”—on stage, artificial intelligence is
everywhere.
In
its recent long-term workforce plan, the NHS spells out the support on offer through AI, to
a staff who are exhausted, depleted and stretched, trying to treat 1 million
people every 15 hours. But is it ethical? Is it enough? Will it erode, or
enhance, the doctor-patient relationship?
Alarm over AI
In
May 2023, the World Health
Organization called for
caution when using artificial intelligence to help doctors diagnose and make
clinical decisions, through computers that have crunched huge amounts of
patient data to make models and predict patterns of disease. The technology
needs vetting, validating and verifying for safety: “untested systems could
lead to errors by health-care workers, cause harm to patients, erode trust in
AI and thereby undermine (or delay) the potential long-term benefits and uses
of such technologies around the world,” says the WHO.
"The technology needs vetting, validating and verifying for safety"
They
also ask about the human data used to train AI. Was consent given by patients
to dissect their data in this way? How diverse is the data? Does it cover a
broad cross-section of society, or might it be biased and not inclusive? Might
it be misused to spread disinformation about disease?
Harvesting the health benefits
Since
2020, the NHS has been monitoring the progress of AI in healthcare through its
“AI-Lab”. More than £100 million has been invested in 86
projects, including those that relate to cancer, stroke, respiratory and skin
diseases.
With
112,000 job vacancies in the NHS, it’s hoped that AI can free up staff time and
improve efficiency. Some administrative tasks can be automated; speech
recognition technology serves as a virtual scribe; scans can be seen and images
interpreted by AI in the first instance; and drugs dispensed and surgery
assisted by robots. In the emergency department, it’s estimated that a minute cut from each patient consultation
would free up 400,000 extra hours each year; a similar shaving would release
5.7 million hours of GP appointment time.
"In the emergency department, a minute cut from each patient consultation would free up 400,000 extra hours each year"
“DOC@HOME” technology allows blood pressure and other readings to be sent
to the doctor, so that signs of sickness are spotted sooner, while unnecessary
appointments are avoided. AI can also analyse facial features, identifying
signs of pain in people who are otherwise unable to voice their pain; acoustic
monitoring picks up sounds from care home bedrooms, alerting to falls or fits
or calls for help.
Balance
is needed, though, between AI in the healthcare setting and human creativity,
critical thinking and intuition. The tone of a voice and the touch from a hand
can meanwhile communicate a message of reassurance and comfort that technology
never can, especially in dementia when spoken words may have lost their meaning.
Homing in on the heart
“Our
new AI reads complex heart scans in record speed, analysing the structure and
function of a patient’s heart with more precision than ever before. The beauty
of the technology is that it replaces the need for a doctor to spend countless
hours analysing the scans by hand” says consultant cardiologist Dr Rhodri
Davies, reflecting on the new AI scanner that takes just 20 seconds to scan a
patient, compared to the 13 minutes or so taken by a doctor to manually analyse images
from an MRI scanner. It’s also more precise than the human eye and can help
diagnose heart disease, and possible damage to the heart during chemotherapy.
ECGs (tests to check your heart rate and rhythm) can
also be analysed by AI—an improvement on the computer programs which have long
been used to do this, but which do not always capture the complexity and
nuances of an ECG.
Hannah Smith, from the Department of Computer Science
at Oxford University, is working with AI to further improve the way that ECGs
are interpreted, since there is concern that ECGs are misread and misdiagnosis
made, if a person’s ECG is not adjusted according to their unique body size and
shape.
"AI tools are being trained with thousands of MRI scans to make 3D images of chests and hearts"
“When
sensors are stuck to a person’s bare chest to read the ECG, they sit at very
different angles and distances from the heart depending on the geometry of the
patient’s upper body, and the heart itself, complicating the ECG reading,”
explains Hannah.
AI
tools are being trained with thousands of MRI scans to make 3D images of chests
and hearts; Hannah is using a mixture of statistics and mathematical modelling
to then learn how the shape of the heart and torso relates to the ECG, so that
future ECG tests can be tailored to each person’s true anatomy, giving an
accurate reading of the heart’s electrical activity. “This can be especially
important when it comes to women, because their hearts are smaller and
differently located, making the tell-tale signs of serious heart attacks more
subtle, so easier to miss”.
Dangerous
heart rhythms are sometimes left undiagnosed, leading to sudden arrhythmic death syndrome (or SADS), when someone dies suddenly and
unexpectedly because of cardiac arrest. Improving interpretation of irregular
heartbeats is one example of how AI can be good news in medicine.
Banner credit: ipopba
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