DeepMind can now detect eye diseases as accurately as human doctors
Working with London-based Moorfields Eye Hospital and UCL’s Institute of Ophthalmology, the results of the preliminary research, published in Nature, can pave the way for the rollout of AI systems in hospitals across the country.
DeepMind’s AI aims to drastically reduce the time doctors spend studying thousands of optical coherence tomography (OCT) eye scans, and can diagnose patients within seconds. Moreover, Moorfields Eye Hospital says the technology can recommend the best path of treatment for more than 50 diseases with 94% accuracy.
“The number of eye scans we’re performing is growing at a pace much faster than human experts are able to interpret them,” said Dr Pearse Keane, consultant ophthalmologist at Moorfields Eye Hospital. “There is a risk that this may cause delays in the diagnosis and treatment of sight-threatening diseases, which can be devastating for patients.
“The AI technology we’re developing is designed to prioritise patients who need to be seen and treated urgently by a doctor or eye care professional. If we can diagnose and treat eye conditions early, it gives us the best chance of saving people’s sight. With further research, it could lead to greater consistency and quality of care for patients with eye problems in the future.”
How DeepMind is proving as effective as clinicians
OCT scans produce a 3D map of the back of the eyes, which trained clinicians must manually examine to identify the key features of eye diseases and make a diagnosis. Conventionally, they have been challenging to interpret and have proven time-consuming, but DeepMind says its technology can analyse these scans within seconds and make recommendations instantly.
Clinicians studied the same OCT scans that were fed into the DeepMind system and made independent recommendations to establish whether the AI was making correct referrals. The study concluded it was able to make the correct referral with a very high level of accuracy.
How a user interacts with DeepMind’s OCT viewer
DeepMind’s AI has also been structured in such a way as to avoid the “black box problem” of understanding how the technology works. Given how important it will be for clinical staff and patients to understand how these decisions are reached, the system – which operates using two neural networks – shows visuals of the eye disease it has identified and the percentage of how confident its treatment recommendation is.
“While we’re incredibly proud of this progress, this initial research would need to be turned into a product and then undergo rigorous clinical trials and regulatory approval before being used in practice,” a DeepMind spokesperson said.
“But we’re confident that, in time, this system could transform the diagnosis, treatment and management of eye disease. Our partners at Moorfields want our research to help them improve care, reduce some of the strain on clinicians, and lower costs – all at the same time. So we’ve also worked hard on what comes next.”
This milestone marks the end of the first phase of a partnership struck between Moorfields and DeepMind two years ago. DeepMind is hoping, following further research and approval, that its AI technology can be deployed in Moorfields’ more than 30 UK hospitals and community clinics, serving 300,000 patients a year.