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| EDITORIAL |
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| Year : 2023 | Volume
: 11
| Issue : 2 | Page : 75-76 |
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Modernizing ophthalmology: The transformative role of artificial intelligence
Rajesh Subhash Joshi
Editor, Journal of Clinical Ophthalmology and Research; Department of Ophthalmology, Government Medical College, Nagpur, Maharashtra, India
| Date of Submission | 13-Apr-2023 |
| Date of Decision | 17-Apr-2023 |
| Date of Acceptance | 21-Apr-2023 |
| Date of Web Publication | 27-Apr-2023 |
Correspondence Address:
Rajesh Subhash Joshi
Editor, Journal of Clinical Ophthalmology and Research; Department of Ophthalmology, Government Medical College, Nagpur, Maharashtra
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jcor.jcor_49_23
How to cite this article:
Joshi RS. Modernizing ophthalmology: The transformative role of artificial intelligence. J Clin Ophthalmol Res 2023;11:75-6 |
How to cite this URL:
Joshi RS. Modernizing ophthalmology: The transformative role of artificial intelligence. J Clin Ophthalmol Res [serial online] 2023 [cited 2023 Jun 8];11:75-6. Available from: https://www.jcor.in/text.asp?2023/11/2/75/374871 |
Vision is the art of seeing what is invisible to others – Jonathan Swift.
Gone are the days of the long queues at the railway station, check-in at airports, booking taxis for traveling, movie tickets, scheduling consultations with physicians, offline shopping, and so many tasks. Life has become easy due to the development of computers and artificial intelligence (AI). With AI, we can set reminders, automatic messages sending, automatic light systems, security cameras, and so on. Our routines have become easier. Overall, AI has transformed our daily lives, making them more expedient, tailored, and resourceful. The concept of AI is considered to have emerged at the Dartmouth Summer Research Project in 1956.[1] AI is used to mimic intelligent human behavior.
We always aim for newer technology due to its improved performance, faster processing speed, high level of accuracy, improved security, better user experience, enhanced workflow, better accessibility, and lower costs as it is adopted by the masses.
It helps streamline processes, automate repetitive tasks, and reduce the time and effort required to accomplish the work.
When the COVID-19 pandemic struck, the entire health-care system was clueless about the clinical features, investigations, and treatment. AI came in a big way to solve these issues. AI was used for DNA sequencing using Convolutional Neural Networks.[2] AI-based drug discovery pipeline was used to generate a cost-effective new drug compound.[3] It also helped to develop predictive models for the disease, such as the likelihood of hospitalization or death, so that physicians can identify high-risk patients and allocate resources effectively. The Pandemic accelerated the development and adoption of AI in health care. Looking at the opportunities Indian Government launched National AI Portal. One stop platform for all information related to AI. These include AI start-ups, research papers, policies, and training programs. It has also been used to manage traffic violations in real time in Jaipur city. Swayam platform launched by the Indian government offers personalized learning recommendations to students based on their learning preference and performance.
Ophthalmology is not lagging in this sector. Many innovations are occurring in ophthalmic subspecialties. AI-powered systems are being used to analyze retinal images and detect diabetic retinopathy without the need of clinicians' interpretation.[4] AI algorithms are also useful for in-home monitoring of age-related macular degeneration. AI is also being used to detect glaucoma through analysis of optic disc images and optical coherence tomography. Possibly, AI was used initially for retinal diseases and diagnosis of glaucoma. It has recently been explored in the field of anterior segment diseases and conditions such as cataract, refractive errors, and corneal infections. Looking at the burden of these diseases globally, AI will be of great help.
India has also made its mark in the AI sector. Prime institutes in India are geared up to develop system for ocular disease detection with high degree of accuracy, enabling early intervention and treatment.
However, every technology comes with disadvantages and challenges when propelled into the market. There is always the fear of dependence on technology. With increasing reliance, there is the risk of reduced human involvement and overdependence on technology. The personal touch will be lost, and during difficult times, there will be a lack of emotional support.
While diagnosing the conditions, if the AI system is trained in biases, it can expand them. This may result in the unjust treatment of individuals or groups which fall into that category.
If AI becomes more prevalent in health-care systems, ethical considerations need to be addressed. Patient privacy, data security, and accountability need to be contemplated. AI should be used for the benefit of patients and not for exploitation.
Every technology comes with a cost. The cost of development, upgradation, and launching will be huge.
It is unlikely to replace the clinician's role. However, it is likely to enhance patient care by improving diagnostic performance and predicting potential outcomes.
India is shining, and so is Indian Ophthalmology.
AI has the potential to revolutionize the way we diagnose eye diseases, bringing us closure to a world where preventable blindness will soon be a thing of the past – Unknown.
| References | |  |
| 1. | Kline R. Cybernetics, automata studies, and the Dartmouth conference on artificial intelligence. IEEE Ann Hist Comput 2011;33:5-16.  |
| 2. | Lopez-Rincon A, Tonda A, Mendoza-Maldonado L, Mulders DG, Molenkamp R, Perez-Romero CA, et al. Classification and specific primer design for accurate detection of SARS-CoV-2 using deep learning. Sci Rep 2021;11:947. |
| 3. | Zhavoronkov A, Aladinskiy V, Zhebrak A, Zagribelnyy B, Terentiev V, Bezrukov DS, et al. Potential COVID-2019 3C-like protease inhibitors designed using generative deep learning approaches. ChemRxiv. Preprint. Available from: https://doi. org/10.26434/chemrxiv. 2020;11829102:v2. |
| 4. | Abràmoff MD, Lavin PT, Birch M, Shah N, Folk JC. Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices. NPJ Digit Med 2018;1:39. |
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