search.noResults

search.searching

dataCollection.invalidEmail
note.createNoteMessage

search.noResults

search.searching

orderForm.title

orderForm.productCode
orderForm.description
orderForm.quantity
orderForm.itemPrice
orderForm.price
orderForm.totalPrice
orderForm.deliveryDetails.billingAddress
orderForm.deliveryDetails.deliveryAddress
orderForm.noItems
LABORATORY INFORMATICS


AI driven real-time diagnosis


SOPHIA KTORI DISCUSSES AN AUTONOMOUS ARTIFICIAL INTELLIGENCE (AI) PLATFORM FOR DETECTING DIABETIC RETINOPATHY WITH MICHAEL ABRAMOFF, FOUNDER AND EXECUTIVE CHAIRMAN OF IDX


In January 2020 the American Diabetes Association released a new set of clinical standards that,


for the first time, included the use of an FDA-approved autonomous artificial intelligence (AI) platform for detecting diabetic retinopathy in people with diabetes. The system, IDx-DR, has been developed by Iowa-based IDx Technologies, and can carry out a clinical diagnosis from retinal images, in real time. FDA approved the autonomous AI technology that underpins IDx-DR in April 2018, through a 510k de novo authorisation process. And it’s the term autonomous that’s key


here. ‘Our system is the only autonomous AI, in any industry, that is available to the public in the US,’ commented Michael Abramoff, founder and executive chairman of IDx. ‘You can’t yet buy a self-driving car and take it on public roads, and you won’t get a loan decision from an AI software without a human overseeing it. As a completely autonomous AI system, IDx-DR is FDA-approved to make clinical decisions without any human oversight whatsoever.’ The analysis for diabetic retinopathy


is carried out on two retinal images per eye, obtained using a standard fundus camera. The images are transferred by the operator, via computer, to the IDx-DR analysis system. However, rather than being assessed by an ophthalmologist or specially trained practitioner, the images are analysed solely by the IDx-DR platform – which, within seconds, provides either a positive or negative clinical decision, together with follow-up care instructions. If the images are of sufficient quality,


the software provides one of two results: either ‘more than mild diabetic retinopathy detected: refer to an eye care professional’,


22 Scientific Computing World Spring 2020


or, ‘negative for more than mild diabetic retinopathy; rescreen in 12 months.’ If the image quality isn’t high enough, the system guides the operator through retaking an image. The system can directly interface with other medical software and healthcare records, so it can be implemented rapidly into healthcare environments where patients may otherwise have to wait months before an appointment with an ophthalmologist becomes available, comments Abramoff. It’s because IDx-DR is the first


completely autonomous AI to be cleared for public use that the regulatory approval process has thrown up a whole raft of clinical trials-related, regulatory, and insurance-related considerations and hurdles – technological factors aside – that have taken Abramoff and his company nearly 10 years to negotiate. ‘We had to work closely with FDA to


secure the most appropriate testing route for approval, as well as work with the US healthcare system and insurance providers,’ Abramoff noted. Issues around insurance have been particularly interesting. ‘We assume full liability for the AI’s performance – just as a physician has for their decisions - so it was of huge interest to all developers of autonomous AI technologies, and not just those in the healthcare field, to see how we would be insured, what is the chain of liability, etc. and how potential litigation may play out.’ Getting a truly autonomous AI system


into the clinical decision-making arena was a huge achievement, Abramoff acknowledged, not just because of the insurance issue. FDA had never approved an autonomous AI system, so this was breaking new ground on many fronts.


‘We had two options, then, for our first market approval,’ Abramoff noted. ‘We could go to a country with a less stringent regulatory process, perhaps in the developing world, get the experience and test the platform on more patients in those real-world settings, and then go back to the US and seek FDA approval as a second stage. Or, we could take the road less travelled, and go straight to the US as our first market and negotiate FDA approval.’ It was this latter option that IDx took, and


Abramoff, who is a clinical ophthalmologist, spent eight years working with FDA on how to validate the platform and how to design and test the algorithm, demonstrate that the system was safe, efficient, effective and equitable, and that it would negate the potential for racial bias.


The algorithm underpinning the IDx-


DR platform is designed to mimic how clinicians might look at images. ‘They look


“As a completely autonomous AI system IDx-DR is FDA-approved to make clinical decisions without any human oversight whatsoever“


for certain biomarkers, and so we build systems that mimic that. But, because we use deep learning very directly, we can go way deeper and pry apart what is actually going on with the disease at the finest level, to mimic how the physician analyses the images.’ Importantly, the clinical trial assessing


the IDx-DR system wasn’t designed to directly compare a clinical diagnosis made by autonomous AI with a clinical diagnosis made by an ophthalmologist, Abramoff continued. Rather it was designed to measure patient outcomes. ‘After all, that’s the bottom line,’ he stressed. ‘Patients don’t want to know if the AI system is better than an ophthalmologist, they want to know if it’s going to improve their lives.’ In reality, long-term, chronic conditions such as diabetic retinopathy, progression may take years and be hard to predict, so


@scwmagazine | www.scientific-computing.com


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32