Kristi Sharma, M.Optom

Education Engagement Manager, Vision Science Academy

Synopsis:

The rise of Artificial Intelligence (AI) brought with it a number of advantages to people in their personal as well as professional lives. However, the other side of it also never ceased to exist. AI gave rise to a large number of concerns in people’s lives and never-ending challenges to professionals, non-medical and medical fields alike. This article explores how AI can help eye care providers in clinical setting, research as well as the academic aspects without necessarily replacing them. It is all just a matter of being conscious users and utilising AI for the benefits of humankind.

Introduction:

When Artificial Intelligence (AI) made a rise in the world of technology, a lot of work became easier. Be it children’s assignments, help with official documents, planning an event, and so on. However, with it, also came the ascending concerns of authenticity, trust and a fear of being replaced. People from various professions across the globe have raised concerns regarding whether AI will replace professionals in the near future.⁽¹⁾ Is this concern necessary? As eye care providers, should we be worried of being replaced by AI?

Image 1: Components of AI

AI as a Powerful Tool for Eye Care

It is well established how AI can be a beneficial asset in the field of eye care.⁽²⁾ Among other, we are aware of the contribution of AI in common ocular conditions like:

1. Diabetic Retinopathy
2. Age Related Macular Degeneration
3. Digital Eye Strain
4. Cataract
5. Dry Eye

This said, how is AI helping out in these types of conditions? AI is being widely used today for screening and detecting common ocular conditions posing threat to public health.⁽²⁾ One of the most common conditions in which AI is extensively used, especially in community screening setups, is Diabetic Retinopathy. In 2018, the first approved AI-assisted DR detection device was approved by the U.S. Food and Drug Administration.^(2,3) The deep neural networks in AI offers higher predictive performance using retinal images for DR screening. Not only in terms of predictability, but AI based models for screening are feasible and acceptable by patients as well.⁽³⁾ However, the highlight here is the fact that AI assists in this detection, rather than deciding alone. This assistance is in the form of being efficient by reducing human errors, analysing multiple inputs at ones while professionals focus more on the aspects of critical thinking and patient interactions.⁽⁴⁾

When it comes to community screening and extensive outreach, AI plays a vital role. Teleophthalmology in conjunction with AI is an extremely powerful innovation for the betterment of community practices.^(5,6,7) Teleophthalmology, which involves extensive outreach in remote locations with the help of telecommunication technology, now widely incorporates AI systems for large scale screening of various ocular conditions requiring immediate attention to avoid vision-threatening complications.⁽⁶⁾ AI systems have shown sensitivity and specificity ranging from 89.5% to 99.1% for various posterior segment diseases.⁽⁸⁾ The increased efficiency of AI systems, avoiding human errors, provides a benefit when it comes to large scale screening by facilitating better patient care and management.

Image 2: Components of AI

Why Clinical Judgement and Human Touch Remain Essential?

The role of an eye-care professional is not just limited to testing, detecting, and treating diseases or conditions. There are certain other traits essential that can never be taken over by any AI systems. We talk here about patient counselling. Counselling a patient about their ocular condition, management options, further steps to be taken, all depends on empathy by the eye care provider.^(9,10) Perfect counselling can only happen when one places themselves in the shoes of the patient, feel the exact emotions that are felt by the patient and by trying to arrive at a decision which is most in favour of the patient. It takes critical thinking to personalise treatment plans for the patient and this can only be done by a human being, not an AI.

Another aspect which requires human intelligence is interpreting patient histories, lifestyles and emotional needs, something that AI cannot do. The understanding of these components is of utmost importance to correctly diagnose and treat any ocular condition and provide optimum care to the patient.⁽¹¹⁾

Image 3: Flowchart showing roles that cannot be performed by AI

Conclusion

This brings us to the conclusion that in a clinical setup, AI helps in assisting eye care providers, rather than replacing them. There are a number of roles that can be efficiently performed by an AI system. However, these duties are solely not enough to formulate total patient care. Collaborative work between AI and eye care providers is crucial to bring out the best possible outcome in terms of patient management.

References

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3. Grzybowski, A., Brona, P., Lim, G., Ruamviboonsuk, P., Tan, G. S., Abramoff, M., & Ting, D. S. (2020). Artificial intelligence for diabetic retinopathy screening: a review. Eye, 34(3), 451-460.
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6. Nikolaidou, A., & Tsaousis, K. T. (2021). Teleophthalmology and artificial intelligence as game changers in ophthalmic care after the COVID-19 pandemic. Cureus, 13(7).
7. Sharma, K. (2024). The Vital Role of Optometrists in Tele-ophthalmology: Enriching Eye-Care for the Community.
8. Wei, Q., Chi, L., Li, M., Qiu, Q., & Liu, Q. (2025). Practical Applications of Artificial Intelligence Diagnostic Systems in Fundus Retinal Disease Screening. International journal of general medicine, 18, 1173–1180. https://doi.org/10.2147/IJGM.S507100
9. Chow, S. C., Lam, P. Y., & Choy, B. N. K. (2022). Patient-centred care in ophthalmology: current practices, effectiveness and challenges. Graefe’s Archive for Clinical and Experimental Ophthalmology, 260(10), 3149-3159.
10. Krishnakumar, R., Anuradha, N., Hussaindeen, M. J. R., & Sailaja, M. V. S. (2016). Role of optometrist in eye hospitals. MEDICAL & VISION RESEARCH FOUNDATIONS, 34(1).
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