How AI can make health care better
Summary
TLDRThe video discusses the growing role of artificial intelligence (AI) in healthcare, particularly in addressing the shortage of doctors and improving patient care. AI is shown to rapidly analyze medical data, such as retinal scans, helping to diagnose diseases more efficiently. The script highlights success stories, such as saving eyesight and heart operations, while also addressing concerns around patient privacy and the 'black box' nature of AI decision-making. AI is seen as transformative, potentially speeding up medical procedures, trials, and innovations, but challenges remain in ensuring transparency and accountability.
Takeaways
- 🤖 AI has the potential to revolutionize healthcare by transforming diagnosis and treatment processes.
- 🧑⚕️ There is a global shortage of doctors, leading to delays in patient care, particularly in fields like ophthalmology.
- 👁️ AI systems can diagnose over 50 types of eye diseases quickly, which could prevent many patients from going blind due to treatment delays.
- 🌍 By 2050, vision impairments are expected to increase by 50%, making the role of AI in diagnostics more crucial.
- 🔬 AI's ability to process and analyze medical data faster than humans could improve diagnoses across multiple fields of medicine.
- ⚠️ Privacy concerns remain a challenge, as illustrated by legal actions against DeepMind over inappropriate use of NHS patient data.
- 🔒 New AI technologies like Bitfount aim to improve data privacy while enhancing patient care by allowing data to stay within hospitals.
- 🏥 AI can potentially speed up the testing of medical procedures, such as simulating heart valve replacements before surgery.
- 💡 Empowering clinicians to develop their own AI models could lead to new discoveries in disease patterns and more personalized treatments.
- 💻 Virtual trials using AI can significantly reduce the time and cost of clinical trials, accelerating the development of new medical devices.
Q & A
What is the main medical problem highlighted in the script?
-The main medical problem is the growing number of patients and a shortage of doctors to treat them, leading to delays and inadequate care in healthcare systems worldwide.
How can AI potentially revolutionize healthcare?
-AI can transform healthcare by diagnosing and treating patients more efficiently, making medical procedures and trials faster and more effective, and handling large volumes of patient data that human experts cannot manage in a timely manner.
What specific eye condition is discussed in the script, and how has AI been involved?
-The script discusses age-related macular degeneration, the most common cause of blindness in the UK and US. AI has been developed to diagnose over 50 types of eye diseases quickly, significantly improving diagnosis speed compared to human doctors.
What are some of the risks associated with delayed eye care as mentioned in the script?
-Delays in eye care can result in irreversible blindness, as some patients are not seen and treated promptly due to overwhelming numbers of appointments, as highlighted by cases of patients losing their vision while waiting for care.
How does the AI system improve the diagnosis of eye diseases?
-The AI system can analyze retinal scans within seconds, identifying various disease features much faster than human experts, who may take hours or even days to complete the same task.
What are some concerns about using AI in healthcare, as discussed in the script?
-Concerns include threats to patient privacy, especially in cases where AI companies like Google DeepMind have mishandled sensitive medical data. There are also worries about accountability and interpretability when using AI models, as they often operate as 'black boxes' with complex, opaque decision-making processes.
How does the collaboration with machine learning startup Bitfount aim to address data privacy issues in AI healthcare applications?
-Bitfount's technology acts as a secure switchboard, allowing queries to be sent to data without the data leaving its home location, such as a hospital. This helps maintain patient privacy and reduces the risk of data misuse while still enabling AI-driven analysis.
What potential benefits does AI offer in the development and approval of new medical treatments?
-AI can speed up the testing and approval of new treatments by using privacy-preserving techniques, automating data analysis, and reducing the time required to conduct trials, ultimately bringing better medical solutions to patients faster.
How is AI being used to recognize patterns that are invisible to human experts?
-AI has been developed to recognize patterns in retinal scans, such as identifying a person’s gender, which is something human experts cannot do. This ability could lead to further discoveries in disease patterns and biomarkers.
What are virtual trials, and how do they benefit the testing of new medical devices?
-Virtual trials use AI to create digital replicas of patients, allowing multiple variations of new procedures or technologies to be tested without posing any risk to real patients. This approach speeds up trials, reduces costs, and helps identify the best treatments more efficiently.
Outlines
🩺 AI in Healthcare: A Solution to a Growing Medical Crisis
The global healthcare system is struggling with an increasing number of patients and a shortage of doctors. Artificial intelligence (AI) is emerging as a potential solution, with the ability to revolutionize diagnostics and treatment. AI can expedite the development and testing of medical procedures, offering significant benefits. Elaine Manor, a patient with age-related macular degeneration, shares her experience of regaining vision through successful treatment. However, many patients face delays in treatment, leading to severe consequences. Dr. Keen and his team have developed AI systems capable of diagnosing over 50 eye diseases swiftly, providing a much-needed answer to the overwhelming patient load. AI’s potential extends beyond ophthalmology, as it can process vast amounts of data rapidly, promising improvements in various medical fields.
🔒 Enhancing Patient Privacy While Integrating AI
The challenge of integrating healthcare data across different medical institutions hinders comprehensive patient care. Dr. Keen’s collaboration with Bitfont, a machine learning startup, aims to improve data connectivity and patient privacy. Bitfont’s technology functions as a switchboard, allowing data to remain at its source while enabling necessary inquiries, thus ensuring data security. This innovation could accelerate the approval of new treatments, addressing current delays in bringing ideal medical solutions to market. The healthcare sector anticipates significant growth in AI’s value, potentially empowering clinicians to independently develop AI models, fostering new discoveries in disease patterns and biomarkers. By 2027, the healthcare AI market is expected to be eight times larger than in 2020.
🩻 Virtual Trials: Revolutionizing Medical Testing
AI is transforming the testing of new medical devices through virtual trials, reducing the time and cost required for clinical research. Dr. Blackman and Professor Frangie at the University of Leeds have developed a method to create 3D digital replicas of patients, allowing multiple treatment scenarios to be tested on the same virtual model. This approach has proven to be as effective as traditional trials, but significantly more efficient. The team's virtual trials produced results comparable to three clinical trials in just three months, at a fraction of the cost. While virtual trials cannot replace human trials, they offer a powerful tool for accelerating the development and testing of new medical technologies.
Mindmap
Keywords
💡Artificial Intelligence (AI)
💡Retinal Scans
💡Macular Degeneration
💡Patient Data Privacy
💡Virtual Trials
💡Healthcare Ecosystem
💡Deep Learning
💡AI in Medicine
💡Bitfount
💡Age-Related Vision Impairment
Highlights
AI has the potential to revolutionize healthcare by transforming the ways patients are diagnosed and treated.
Artificial intelligence can diagnose over 50 types of eye diseases as well as doctors, but in much less time.
Age-related macular degeneration is the most common cause of blindness in the UK and the US, impacting millions globally.
AI can analyze retinal scans in seconds, while human specialists may take hours or days.
An estimated 596 million people had distance vision impairment worldwide in 2020, and by 2050, that number is expected to rise by 50%.
AI's ability to process and analyze large amounts of medical data quickly can lead to more efficient diagnoses across various fields.
AI offers solutions to the growing global challenge of doctor shortages and overwhelming patient numbers, especially in eye care.
There are concerns about patient privacy, particularly after DeepMind, Google’s AI company, faced legal action over its use of NHS patient data.
Bitfount, a new AI platform, aims to improve patient privacy by ensuring medical data never leaves its original location.
Virtual trials powered by AI could significantly reduce the time and cost of testing new medical devices, speeding up the approval of treatments.
AI has been used to create a code-free deep learning model that can identify gender from retinal scans, something human experts cannot do.
AI could potentially empower clinicians to develop their own diagnostic tools, bringing them closer to patient needs.
The growth of AI in healthcare is expected to be eight times bigger by 2027 compared to 2020.
AI 2.0 aims to integrate prior knowledge, such as physics and physiology, with data, leading to more accurate and knowledge-driven healthcare systems.
AI in healthcare will continue to evolve, enhancing both patient care and the development of new medical treatments through more sophisticated models.
Transcripts
the world is facing a big medical
problem
a growing number of patients
and not enough doctors to treat them
so could artificial intelligence be the
cure i feel like i'm working at the
forefront of something that could
potentially be revolutionary to
healthcare in the future ai has the
power to transform the ways patients are
diagnosed and treated when we think
it'll become a game changer and to make
the testing of new medical procedures
more efficient and effective if we can
get devices that can be developed faster
better
and quicker
then there are huge benefits
[Music]
elaine manor is blind in one eye
she is a victim of age-related macular
degeneration
the most common cause of blindness in
the uk and us
when it went to my other eye i was just
terrified i was in bits i was weeping in
the rain and
thinking i don't want to be here
[Music]
for years the threat of losing her other
eye has loomed large
until a successful treatment enabled the
thankful 75 year old to see her way to
some high wire fundraising
i did the high sick wire in europe
i did the sky dive
and then i did the the wing walk
[Music]
but the doctor who saved elaine's eyes
says she is one of the lucky ones nearly
10 of all clinic appointments in the nhs
are for eyes that's nearly 10 million
appointments per year so to put it
brutally we're almost drowning in the
number of patients we need to see
and as a result of that there are some
patients unfortunately who go blind
because of delays in being seen and
treated a pregnant mother was left
almost completely blind waiting for care
she has since given birth and has never
seen her daughter's
face dr keen
believes there's an answer
artificial intelligence
he and his partners have developed ais
which can diagnose over 50 types of eye
disease just as well as a doctor
but do so
much much more quickly the ai system can
analyze the retinal scans within seconds
and it can delineate all of the
different disease features on the scans
a human expert would probably take hours
or even days to complete the same task
ai can help to address a growing global
challenge
in 2020
an estimated 596
million people had distance vision
impairment worldwide
of whom 43 million were blind
by 2050 both these figures are set to
increase by approximately 50 percent
a task that can take specialist doctors
hours now being done in seconds through
artificial intelligence and it's not
just eyesight ai's ability to mine and
analyze patient data far more quickly
than humans can mean diagnoses could
improve in many areas of medicine we do
more than a thousand scans per day in
the hospital it's a challenge because
where do we get the the human experts to
be able to review all those scans but
it's also an opportunity because that
huge amount of data is the perfect
substrate for the development of
artificial intelligence systems
but there are concerns
in particular threats to the privacy of
patients
deepmind google's ai company and one of
dr keane's partners has found itself
under fire
google deep mind the search giant's
artificial intelligence arm may have
received the personally identifying
medical records of 1.6 million nhs
patients here at the royal fair hospital
on a legally inappropriate basis
unrelated to its work with dr keane
deepmind is currently facing legal
action over its use of nhs data
yet if data can be better protected
ai has the capacity to make patient care
much better
and more efficient
so we have a world that is essentially
very much connected
but yet healthcare data is siloed
we can order a taxi from almost anywhere
in the world using our smartphones
but yet if we have a patient who comes
to an eye hospital like moorefields but
they're also attending a hospital
because they've got cancer we often
can't easily connect their data
dr keen hopes his latest collaboration
with machine learning startup bitfont
could not only join data dots better but
also improve patient privacy with fount
is is a kind of switchboard all we do is
essentially pass messages between
someone who wants to ask something of
the data set and the owner of the data
the data
never never leaves its home location so
if that data is held by a hospital
no data ever leaves the hospital bitfont
says this technology could have other
benefits like approving new treatments
more quickly and safely patients are
losing out a lot by the fact that ideal
medical treatments for them are not
coming through to to market
with the extra technical guarantees that
privacy preserving techniques like
bitfont can provide there's been a real
feeling around the healthcare ecosystem
that that could speed up a lot of those
governance processes
by 2027
ai's value in the healthcare market is
expected to be eight times bigger than
in 2020 growth could also be boosted if
clinicians reduce their dependence on
coders and start to develop their own ai
systems
this is really exciting because today's
retinal experts have been unable to
identify gender dr kira o'bern is part
of a team of clinicians who have managed
to do what google brain did in 2018
develop ai that can recognize gender
from retinal scans
something no human can do
a member of our research group developed
a code-free deep learning model which
accurately identified gender from
rational images
this is incredibly exciting because by
positioning clinicians
to develop their own models
independently it could really open the
door to further discoveries in both
disease patterns and disease biomarkers
a new generation of doctors believe
empowering clinicians in this way will
bring them closer to patients
generally it's the clinician that's the
healthcare workers working face-to-face
with the patient to understand what the
patients need best
so therefore i believe that if we can
allow them to independently develop
their own tools this will allow the
patient to remain at the very forefront
of everything
it's the world's first hand-held
battery-powered computer able to hold
thousands of data points i think that
we're potentially at a tipping point a
little bit like the tipping point that
we saw in the late 1970s in the
computing industry we had the
introduction of the first personal
computers if you empower people with
this technology even if primitive in the
beginning they will come up with
hundreds or even thousands of
applications that the engineers would
never have thought of
but some are skeptical about pinning
hopes too fast on ai
the issue is that ai models are
essentially black boxes and so what
happens is that when they're working
well they're working well and no
questions are asked but what happens if
a wrong decision is made what happens
when something goes wrong and how do we
really trace that back and ensure
accountability and guarantee
interpretability if we're using these
black box models
while it is early days for ai in
medicine it could also improve the
testing of new medical devices
a long time ago
a million years bc
everything was
absolutely free
in 2021 former part-time singer and
model patricia walker had an artificial
valve inserted into her heart to save
her life i needed a new valve
because the one that i had wasn't
working it was dripping this is why i
was feeling
the pain that i was getting the
exhaustion and it it was getting
worse
although patricia's operation was a
success
it was not without risk and the
cardiologist who inserted the valve says
ai can make new technologies like this
safer for patients
by creating virtual trials
if we can plan a procedure by simulating
that procedure in an individual patient
in a computer-generated model before we
go to the patient then we can get a much
better outcome in the patient without
posing any risk to that patient at all
at the university of leeds dr blackman
is collaborating with professor alex
frangie he is using machine learning to
automate the building of
three-dimensional digital replicas this
is the real one
and this is the fake one
but it's very difficult to the naked eye
to to pick that up
virtual trials mean multiple variations
of a proposed new procedure or
technology can be tried out we can test
different scenarios of treatment on the
same
anatomy and physiology of a given
virtual individual and that's something
which is not again possible to do with
conventional trials
we're also comparing different scenarios
of hypertensive and normal tensive
conditions
virtual trials do not replace human
trials
but they do speed up the time and reduce
the money required to identify the right
devices and humans to test
in 2021 the team at the university of
leeds found their virtual trials
produced the same results as three
clinical trials but much more
efficiently
each of those studies took between six
and eight years to to be undertaken and
they probably cost around 20 to 30
million each of them so what we showed
is that in this computational study that
the execution of it took about three
months so
that's you know less than
20 grand
some working in the medical world
believe a bright future lies ahead as
ais become more sophisticated and more
capable
in other words more intelligent ai 1.0
in my view is the ability to automate
tasks that otherwise
could be very boring or time consuming
or repetitive
ai 2.0
is the one that actually tries to look
at incorporating prior information on
the physics on the physiology in a much
more intimate manner with the data so
it's not just data driven but it's also
knowledge driven for healthcare it's
hard to see a future without ai
i strongly believe that one day
artificial intelligence
will renew this eye
thanks for watching i'm tom standage
deputy editor of the economist to read
more of our coverage of ai please click
on the link don't forget to subscribe
you
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