[bright music]
Virmani: Hello, I'm Sunny Virmani.
AI may improve outcomes for many diseases and conditions--
perhaps even prevent some.
Today, there are about 415 million diabetic patients in the world.
And each one is at risk of vision loss
due to a terrible disease called diabetic retinopathy,
also referred to as DR.
We spoke to one of our key collaborators, Dr. Kim Ramasamy,
with Aravind Eye Hospital in India
about the disease before pandemic.
In the early stages, it's symptomless.
But that's when it's treatable,
so you want to screen them early on before they actually lose vision.
In the early stages where a doctor is examining the eye,
you take a picture of the back of the eye.
You will see lots of those bleeding spots in the retina.
Today, the doctors are not enough to do the screening.
We have very limited ophthalmologists,
so there should be other ways
where you can screen the diabetic patients for [indistinct] complications.
person: In the U.S., there are about 74 eye doctors
for every million people.
In India, there are only 11.
So just keeping up with the sheer number of patients,
let alone giving them the attention and care they need,
is overwhelming if not impossible.
Vermani: This is a huge problem.
So we wondered, if with the power of machine learning,
we could train a model to read these eye images
captured with a special camera
similar to a trained eye doctor.
This would allow clinics to provide access to eye care
when there is a shortage of physicians.
By partnering with visionaries like Dr. Kim
and with Verily,
we came up with a solution that we call...
Or ARTA.
Using the same technology that powers Google Photos,
we trained it to read retinal images
that doctors had labeled
for diabetic eye disease.
This algorithm proved accurate,
and we worked with the regulators in the EU to get clearance
in 2018.
Since then, we've been working with clinics in India,
Thailand, and the U.S. to see how ARTA
can change the way patients receive care for diabetic retinopathy.
Two of our key collaborators join us from around the world.
First, Dr. Rajiv Raman from Sankara Nethralaya in India.
And Dr. Paisan Ruamviboonsuk from Rajavithi Hospital in Thailand.
Both of them have been instrumental in the development of this technology
and are using it in their clinical settings today.
Thank you for taking time out of our busy day to be with us.
My first question is for both of you.
Please tell us about your experience with ARTA so far,
and how does it change patient care for you?
Let's start with you, Dr. Rajiv.
Raman: Thanks for having me, Sunny.
My research team at Sankara Nethralaya,
a tertiary eye care institute in Chennai,
was involved in the initial development and validation of ARTA.
We also assessed its performance in real time.
Both these studies were also published.
Since 2018,
ARTA is being used across many centers in India,
including of our hospital,
and thousands of people with diabetes have been screened for retinopathy.
You can use it in two modes:
in a fully automatic mode
at places where there's little or no expertise to read the retinal images,
like a primary care physician clinic,
or in an assistant mode
at places where there are ophthalmologists
but can use it to grade retinal images with more confidence
and help reduce the overall burden in providing care.
Virmani: Thank you so much, Dr. Rajiv.
Now, Dr. Paisan, tell us about your experience with ARTA in Thailand, please.
Ruamviboonsuk: Well, thank you, Sunny.
We validated ARTA
for that retinopathy screening
in a retrospective dataset of more than 10,000 retinal images
from patients with diabetes in all healthcare regions in Thailand.
We found ARTA to be more accurate
in detecting that retinopathy
for referral to ophthalmologists compared to the trained graders
who work as retinopathy screeners in Thailand's national screening program.
Now in our prospective study-- this is another study--
ARTA also provided screening results
to patients in [indistinct] during that visit,
rather than having them wait for, like, weeks
to get results to come back from remote ophthalmologists,
as is the case in Thailand.
Now, in this study, ARTA was able to detect
about 50% of patients screened
who had vision-threatening diabetic retinopathy,
and referred them to have treatment.
Virmani: Thanks, Dr. Paisan.
We've been working with you for three years now.
We know building an accurate algorithm is just the first step,
and we need to fully understand how to deploy
any new technology in the field.
What are we learning from these early deployments of using AI
for diabetic retinopathy screening in Thailand?
Ruamviboonsuk: Well, thank you, Sunny. That's a very good question.
Well, I believe an accurate algorithm
was probably the first step.
It is important for the success of ARTA
to ensure a seamless integration
into the clinic workflow,
which we did with our prospective study.
Well, we also have to recognize the skill of the operators,
the screeners, and patient confidence at these clinics
which may impact the quality of images used by ARTA
for providing the correct diagnosis.
Well, we're in the process of understanding
these challenges further
so we can provide a kind of clinical rival
and solution for the screening clinics.
This will also involve a key step of getting regulatory clearance
for ARTA from Thai [indistinct].
Thank you, Sunny.
Vermani: That sounds exciting, Dr. Paisan,
and we're really looking forward to working with you on that.
Now I have a final question for you, Dr. Rajiv.
What does the future of ARTA look like in India?
Raman: India is a home for approximately
77 million people with diabetes,
with the prevalence of diabetes being higher
in the southern part of the country than in the other regions in India.
Currently, there are several ARTA screening programs being conducted,
mainly by the private care providers,
few charitable institutes,
and a very few public health systems of the state.
There is a need of a systematic nationwide screening program
for diabetic retinopathy in India.
ARTA holds a great potential
in playing a key role
in the DR screening in our country
where there is a great mismatch,
a very high load of people with diabetes,
and a significantly less number of ophthalmologists
who can do it in person.
Vermani: That's incredible.
Thank you, Dr. Rajiv and Dr. Paisan
for joining us today and sharing the amazing work you are doing.