Artificial intelligence (AI) can help eye doctors improve the accuracy of their diagnoses, according to a study from the Google AI research group which shows that physicians and algorithms working together are more effective than either alone.
The research, which will be published in the journal Ophthalmology, one of the first to examine how AI can improve physicians' diagnostic accuracy.
This study expands on previous work from Google AI showing that its algorithm works roughly as well as human experts in screening patients for a common diabetic eye disease called diabetic retinopathy.
For their latest study, the researchers wanted to see if their algorithm could do more than simply diagnose disease.
They wanted to create a new computer-assisted system that could "explain" the algorithm's diagnosis. They found that this system not only improved the ophthalmologists' diagnostic accuracy, but it also improved algorithm's accuracy.
Millions of people suffer from diabetes, and are at risk for diabetic retinopathy, a potentially blinding eye disease. People typically do not notice changes in their vision in the disease's early stages.
However as it progresses, diabetic retinopathy usually causes vision loss that in many cases cannot be reversed.
The accuracy of eye screenings can vary significantly. One study found a 49 per cent error rate among internists, diabetologists, and medical residents, researchers said.
Recent advances in AI promise to improve access to diabetic retinopathy screening and to improve its accuracy. However, it is less clear how AI will work in the physician's office or other clinical settings.
Previous attempts to use computer-assisted diagnosis shows that some screeners rely on the machine too much, which leads to repeating the machine's errors, or under-rely on it and ignore accurate predictions.
Researchers at Google AI believe some of these pitfalls may be avoided if the computer can "explain" its predictions.
To test this theory, the researchers developed two types of assistance to help physicians read the algorithm's predictions.
Both types of assistance improved physicians' diagnostic accuracy. It also improved their confidence in the diagnosis. The degree of improvement depended on the physician's level of expertise.
Without assistance, general ophthalmologists are significantly less accurate than the algorithm, while retina specialists are not significantly more accurate than the algorithm.
With assistance, general ophthalmologists match but do not exceed the model's accuracy, while retina specialists start to exceed the model's performance.
"What we found is that AI can do more than simply automate eye screening, it can assist physicians in more accurately diagnosing diabetic retinopathy," said lead researcher Rory Sayres.
"AI and physicians working together can be more accurate than either alone," said Sayres.
(This story has not been edited by Business Standard staff and is auto-generated from a syndicated feed.)