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Artificial Intelligence in Ophthalmology: Current Uses and Future Prospects

by | Jan 1, 2024 | Manuscripts | 0 comments

Kheyali Mondal, B. Optom

Oculoplasty Optometrist, Dr. Shroff’s Charity Eye Hospital, New Delhi, India

 

Introduction:

The word Artificial Intelligence (AI) refers to the general capability of a computer to perform a task with a minimal amount of human participation. The use of this forthcoming technology digitises the field of ophthalmology and thereby increases the vacuity, availability, and productivity of the overall effectiveness of ophthalmology services. (1) It is substantially important to detect diseases of anterior and posterior segment, orbital diseases, and visual field abnormalities. (2)

AI Techniques:

Figure 1: AI Techniques (Image source: self).

Machine learning:

Machine learning derives information grounded on manually named features and classifiers from formerly labeled data which is presented to the machine as a training dataset. This approach can be used with small datasets and requires comparatively shorter training time. (2,3)

Deep learning:

Deep Learning implements the use of an artificial neural network (ANN) which is a complex system containing several layers of artificial neurons mimicking the neural network of the mortal or human brain and its pattern recognition capacities. When input is given to a DL algorithm, it is propagated through the multiple layers of the ANN, and pattern recognition is played by the DL algorithm itself without previously instructed feature selection. (2,3)

AI transforming Eye-care:

Here are four ways AI transition is working in eye care right now:

  1. AI helps in diagnostics. AI-driven tools can provide an advanced level of neutrality and perfection when assessing medical images. (1)
  2. AI is getting a medical mate. New AI tools, like those from Google’s DeepMind, don’t just offer a diagnosis, they explain the disease that has been diagnosed. (3)
  3. AI is helping healthcare providers save time. AI is handling repetitive work, freeing up further time for health care providers, indeed performing more complicated tasks like creating three-dimensional models of ophthalmologic tumors by marking up data from two-dimensional image reviews. (3)
  4. AI is creating new ways for cases to seek care. AI-powered hardware and software solutions are useful to detect and diagnose diseases such as diabetic retinopathy and glaucoma etc.

Future of AI in Ophthalmology:

Multiple studies reported that their AI systems showed excellent performance in detecting eye conditions and could be applied in clinics, although AI-based medical techniques had not yet been authorised for clinical operations for diseases. (3,4)

  • AI could be applied to promote the automated evaluation of other Retinal conditionsfrom clinical images to give timely referrals for positive cases, working on the issues caused by the unstable distribution of ophthalmic medical supplies. (4)
  • AI may directly diagnose diseases of the cornea like keratoconus, forecast their progression and predict IOL power. (3)
  • Artificial intelligence (AI) has become a valuable part of various industries. Recently, it has been tested particularly with LASIK and PRK surgery. (1)
  • AI also could help professionals plot and measure how a person’s disease is progressing. Computer systems can rapidly assess multiple eye scans and compare them. (1,2,4)
  • In the future it will also be at the doorstep of people who cannot reach out to the service and will be working in Teleophthalmology.

 

Conclusion:

An AI algorithm only looks for what you tell it to look for and might miss changes that a human would notice. If a variable changes, the algorithm will have to re-adjust the features. Researchers sometimes can’t explain why one algorithm works when the other doesn’t. For eye care, AI is an investigative new frontier. (5) Artificial intelligence is taking the world by hurricane, and the world of ophthalmology is no exception. AI-based technologies are formerly being used for certain procedures and are now being tested for new ones. (6)

 

Reference:

  1. Hogarty, D. T., Mackey, D. A., & Hewitt, A. W. (2019). Current state and future prospects of artificial intelligence in ophthalmology: a review. Clinical & experimental ophthalmology, 47(1), 128-139.
  2. Du, X. L., Li, W. B., & Hu, B. J. (2018). Application of artificial intelligence in ophthalmology. International journal of ophthalmology, 11(9), 1555–1561.
  3. Li, Z., Wang, L., Wu, X., Jiang, J., Qiang, W., Xie, H., Zhou, H., Wu, S., Shao, Y., & Chen, W. (2023). Artificial intelligence in ophthalmology: The path to the real-world clinic. Cell reports. Medicine, 4(7), 101095.
  4. Jahangir S, Khan HA. Artificial intelligence in ophthalmology and visual sciences: Current implications and future directions. Artif Intell Med Imaging 2021; 2(5): 95-103.
  5. Heger, K. A., & Waldstein, S. M. (2023). Artificial intelligence in retinal imaging: current status and future prospects. Expert review of medical devices, 10.1080/17434440.2023.2294364
  6. Keskinbora, K., & Güven, F. (2020). Artificial Intelligence and Ophthalmology. Turkish journal of ophthalmology, 50(1), 37–43.

 

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