AI detects diabetic blindness
Researchers hope this system will help doctors screen more patients in the country
THE Aravind Eye Hospital will treat anyone who comes through the door, with or without money.
Each day, more than 2000 people arrive from across India and sometimes other parts of the world, crowding into the hallways and waiting rooms of this 43-year-old hospital in the south of the country.
Muthusamy Ramalingamm, a local resident, visited the second floor, where he rested his chin on a small desktop device that pointed a camera into his eyes.
A technician tapped on a screen at the back of an eye scanner, and within seconds a diagnosis appeared on a computer. Both eyes showed signs of diabetic retinopathy, a condition that can cause blindness if untreated.
In most hospitals and clinics around the world, trained physicians make this diagnosis, examining a patient’s eyes and identifying the tiny lesions, haemorrhages and discolouration that anticipate diabetic blindness.
But Aravind is trying to automate the process. Working with a team of Google artificial intelligence researchers based in California, the hospital is testing a system that can recognise the condition on its own.
Google and its sister company Verily targeted this type of blindness because of its prevalence and because it is the sort of illness that an artificial intelligence (AI) system can detect early.
Google is not charging the hospital while it tests the technology.
Researchers hope this AI system will help doctors screen more patients in a country where diabetic retinopathy is increasingly prevalent.
According to the World Health Organisation, about 70 million Indians are diabetic and thus at risk of blindness. But the country does not train enough doctors to properly screen them all.
For every 1 million people in India, there are only 11 eye doctors, according to the International Council of Ophthalmology.
The project is part of a widespread effort to build and deploy systems that can automatically detect signs of illness and disease in medical scans.
Hospitals in the US, Britain and Singapore have also run clinical trials with systems that detect signs of diabetic blindness.
Last month, regulators certified the eye system for use in Europe under the Verily name. The Food and Drug Administration recently approved a similar system in the US. But hospitals are treading lightly as they consider deploying systems that are vastly different from technology traditionally used for health care.
Aravind’s founder, Govindappa Venkataswamy, an iconic figure in India who was known as “Dr V” and died in 2006, envisioned a network of hospitals and vision centres that operate like franchises, systematically reproducing inexpensive forms of eye care for people across the country. There are more than 40 of the vision centres around India.
In addition to screening patients in Madurai – one of the largest cities in southern India – the hospital plans to install Google’s technology in surrounding villages where few eye doctors are available.
Behind the new screening methods are neural networks, complex mathematical systems that can learn tasks by analysing vast amounts of data.
By analysing millions of retinal scans showing signs of diabetic blindness, a neural network can learn to identify the condition on its own.
A neural network is the same technology that is rapidly improving face recognition services, talking digital assistants, and instant translation services like Google Translate.
Because these systems learn from enormous amounts of information, researchers are still struggling to completely understand how they will ultimately behave. But some experts believe once they are honed, tested and properly deployed, they can fundamentally improve health care.
At Aravind, computer screens mounted on the walls of the waiting rooms translate information into the many languages spoken in the hospital.
During his examination, 60-yearold Ramalingamm spoke Tamil. He said he was comfortable with a machine diagnosing his eye condition, in part because it happened so quickly. After the initial screening by the AI system, doctors could treat the eyes, perhaps with laser surgery, to stave off blindness.
The system performs on a par with trained ophthalmologists, according to a study published in the Journal of the American Medical Association. But it is far from completely replacing a doctor.
Today, in these vision centres, technicians take eye scans and send them to doctors in Madurai for review.
The technology still faces regulatory hurdles in India, in part because of the difficulty of navigating the country’s bureaucracy. And though Google’s eye system is certified for use in Europe, it is still awaiting approval in the US.
Luke Oakden-rayner, director of medical imaging research at the Royal Adelaide Hospital in Australia, said these systems might even need new regulatory frameworks because existing rules weren’t always sufficient.
“I am not convinced that people care enough about the safety of these systems,” he said.
Though these deep-learning systems are new, they are hardly the first effort to aid diagnosis through computer technology.
“On paper, the Google system performs very well,” Oakden-rayner said. “But when you roll it out to a huge population, there can be problems that do not show up for years.”