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Honestly, I don't know what to think. Ophthalmology is a great field for AI researchers (lots of images: the eye is an organ that you can photograph and analyze visually in every angles, almost like in dermatology). In Ophthalmology, diabetic retinopathy is an evident take : lots of people involved, lots of annotated pictures available, screening programs.

However, I would like to see the performances of the algorithm on different fundus camera. It is also important to realize that diabetic retinopathy classification is very easy to learn, to the point that if the screening is such a problem, it is easier to ask the person that takes the pictures (In France, a nurse or an orthoptist) to phone the doctor when he/she sees something strange on the eye fundus.



Do you happen to know of a dataset that contains a fundus picture of the back of the eye plus a regular high-res photo of the full eye?




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