Ophthalmologists, Except Pediatric

Today’s AI tools mainly assist ophthalmologists with eye scans and images, not replace them. For example, studies report that AI programs can analyze retina photos or OCT scans to spot signs of disease (like diabetes-related changes or glaucoma) with accuracy close to an expert doctor ^{[1] [1]}. In practice, this means AI is used as a “second pair of eyes” – it flags possible problems so the doctor can confirm them.

By contrast, tasks that need personal judgment or patient interaction – such as writing a prescription for eyedrops or pain medicine, fitting glasses or contacts, giving post-op care, or leading a care team – are still done by people. (In fact, one review noted that designing special contact lenses is very complex, and AI models are only just beginning to try to predict lens parameters ^[2]). AI can help doctors by crunching data or suggesting ideas, but the doctor’s own decision, hands-on exams, and communication are still essential ^{[1] [2]}.

Why adopt AI? One reason is need and convenience. In many places, there simply aren’t enough eye doctors, so tools that speed up screening are attractive.

For example, using portable cameras plus AI to screen for diabetic eye disease is becoming popular in rural clinics – studies show these systems give image quality and diagnoses comparable to standard equipment ^[1]. Such tools can save time and help catch disease earlier. In fact, eye care experts predict that AI devices for early diagnosis will become part of normal practice in the coming years ^[1].