Can AI detect eye diseases before vision is lost? How technology is changing eye care
New Delhi: Artificial intelligence is increasingly becoming part of modern healthcare, and eye care is one area where the technology has significant potential. Eye examinations can produce large amounts of visual information through retinal photographs, scans and other imaging techniques. AI systems can analyse these images and identify patterns that may be associated with certain eye diseases.
This could help doctors detect some conditions earlier, particularly when the disease may not yet have caused noticeable changes in vision. One of the areas where AI is being studied and used is diabetic eye disease. Retinal photographs can show changes in the small blood vessels and other structures at the back of the eye. AI-based systems can help analyse these images and identify people who may need further assessment by an eye specialist.
How AI can support early detection
AI is also being explored for conditions such as glaucoma, age-related macular degeneration and other retinal disorders. Some systems can analyse retinal images or scans and identify subtle patterns that may be difficult to recognise quickly. This does not mean that AI replaces an eye doctor. Instead, it can function as an additional tool to support screening, prioritisation and clinical decision-making.
One potential advantage is accessibility. In areas where there are fewer eye specialists, technology-assisted screening may help identify people who need a detailed examination. A person whose image is flagged as potentially abnormal can then be referred for further assessment. This can be particularly useful for diseases that may progress without obvious symptoms.
Why clinical assessment remains essential
However, AI in eye care also has limitations. An AI system is only as reliable as the data on which it has been developed and tested. Differences in age, ethnicity, medical conditions, imaging equipment and healthcare settings can affect how well a system performs. A result generated by AI therefore needs to be interpreted in the appropriate clinical context.
Another important consideration is that detecting a possible abnormality is not the same as making a final diagnosis. A comprehensive eye examination may involve a patient’s medical history, vision assessment, eye pressure measurement, retinal examination and other tests. These factors help an eye specialist understand the complete picture.
The future of eye care is likely to involve closer collaboration between clinicians and technology. AI can help process large volumes of information quickly and may support earlier identification of people at risk. Doctors, meanwhile, remain essential for confirming diagnoses, understanding individual circumstances and deciding on treatment.
The biggest benefit of AI may therefore not be replacing doctors but helping them detect disease earlier and manage patients more efficiently. As the technology continues to improve and undergo clinical validation, it could become an increasingly useful part of preventive and personalised eye care.
(By Dr Simakurthy Sriram, Chief Medical Officer, Sankara Eye Hospital, Hyderabad)
Disclaimer: This article is written by the doctor mentioned above. The findings should not be considered medical advice or used for self-diagnosis or treatment. Consult a qualified healthcare professional for personalised guidance.