Northerner
Admin (Retired)
- Relationship to Diabetes
- Type 1
Researchers from the Byers Eye Institute at Stanford University have found a way to use artificial intelligence to fight a complication of diabetes that affects the eyes. This advance has the potential to reduce the worldwide rate of vision loss due to diabetes.
In a study published online in Ophthalmology, the journal of the American Academy of Ophthalmology, the researchers describe how they used deep-learning methods to create an automated algorithm to detect diabetic retinopathy. Diabetic retinopathy (DR) is a condition that damages the blood vessels at the back of the eye, potentially causing blindness.
"What we showed is that an artificial intelligence-based grading algorithm can be used to identify, with high reliability, which patients should be referred to an ophthalmologist for further evaluation and treatment," said Theodore Leng, M.D., lead author. "If properly implemented on a worldwide basis, this algorithm has the potential to reduce the workload on doctors and increase the efficiency of limited healthcare resources. We hope that this technology will have the greatest impact in parts of the world where ophthalmologists are in short supply."
https://www.sciencedaily.com/releases/2017/04/170427190717.htm
In a study published online in Ophthalmology, the journal of the American Academy of Ophthalmology, the researchers describe how they used deep-learning methods to create an automated algorithm to detect diabetic retinopathy. Diabetic retinopathy (DR) is a condition that damages the blood vessels at the back of the eye, potentially causing blindness.
"What we showed is that an artificial intelligence-based grading algorithm can be used to identify, with high reliability, which patients should be referred to an ophthalmologist for further evaluation and treatment," said Theodore Leng, M.D., lead author. "If properly implemented on a worldwide basis, this algorithm has the potential to reduce the workload on doctors and increase the efficiency of limited healthcare resources. We hope that this technology will have the greatest impact in parts of the world where ophthalmologists are in short supply."
https://www.sciencedaily.com/releases/2017/04/170427190717.htm