Ana Clara Coelho Caetano¹, Bianca Pessoa Macedo¹, Denyse de Oliveira Moraes Saunders¹, Guilherme Pinheiro Diógenes¹, Liana Maria Feitosa Carvalho¹, Luana Maria Ramalho Castro Siqueira¹, Paulo Victor Castro de Oliveira¹ and Juliana de Lucena Martins Ferreira²

¹Student (a) of the Faculty of Medicine Unichristus, Brazil
²Professor (a) of the Unichristus Medical School, Brazil

*Corresponding Author: Ana Clara Coelho Caetano, Student (a) of the Faculty of Medicine Unichristus, Brazil.

Received: May 15, 2023; Published: June 22, 2023

Abstract

Introduction: Artificial intelligence (AI) is a technology that can help in the analysis of therapeutic procedures, improving the speed, efficiency and accuracy of ophthalmic imaging exams. It is often characterized by the replacement of medical presence by systems such as "Deep Learning" and "Machine Learning", since it has the benefit of cost reduction and the shorter time to obtain imaging results. Given this, artificial intelligence has emerged as a promising resource for ophthalmologists and patients in the screening process.

Objective: The objective of this study was to seek foundations on ophthalmological conditions with the use of AI as well as to evaluate the effectiveness of its use compared to the physical presence of medical professionals.

Methodology: A literary search was performed based on the descriptor: "{(Ophthalmology)} and {(Artificial intelligence)}" in the PubMed and Science Direct databases. In total, 1137 articles were found, from which, after the use of filters and exclusion criteria, 25 articles were selected that related the terms Artificial Intelligence and Ophthalmology and met the objective of this review.

Results and Discussion: Artificial intelligence is being widely used in ophthalmology, proving to be efficient in several ways, such as in the diagnosis and treatment of different pathologies; for example, glaucoma, cataracts, keratoconus and diabetic retinopathy; in ophthalmic surgeries; in the mapping of the cornea and retina.

Conclusion: Although the use of AI in ophthalmology has several advantages, it can be stated that there are still limits regarding its application, such as the lack of qualification of physicians for the use of this tool, the negative perspective related to the unemployment of these professionals - being replaced by the machine - and due to the labor and bioethical situation of the doctor-patient relationship, the presence of a legal apparatus functioning as a brake on the use of Artificial Intelligence in medicine

Keywords: Artificial intelligence; Health Technology; Ophthalmology; Anterior Segment of the Eye; Posterior Segment of the Eye

References

1. BENET David., et al. “Artificial intelligence: the unstoppable revolution in ophthalmology”. Survey of Ophthalmology 67.1 (2022): 252-270.
2. ESENGÖNÜL Meltem., et al. “A Systematic Review of Artificial Intelligence Applications Used for Inherited Retinal Disease Management”. Medicina 58.4 (2022): 504.
3. KAPOOR Rahul., et al. “The current state of artificial intelligence in ophthalmology”. Survey of Ophthalmology 64.2 (2019): 233-240.
4. CATANIA Louis J and NICOLITZ Ernst. “Artificial intelligence and its applications in vision and eye care”. Advances in Ophthalmology and Optometry 3.1 (2018): 21-38.
5. TING Daniel SW., et al. “Deep learning in ophthalmology: the technical and clinical considerations”. Progress in Retinal and Eye Research 72 (2019): 100759.
6. TING Daniel Shu Wei., et al. “Artificial intelligence and deep learning in ophthalmology”. British Journal of Ophthalmology 103.2 (2019): 167-175.
7. TSENG Rachel Marjorie Wei Wen., et al. “Considerations for Artificial Intelligence Real-World Implementation in Ophthalmology: Providers’ and Patients’ Perspectives”. The Asia-Pacific Journal of Ophthalmology 10.3 (2021): 299-306.
8. BALYEN Lokman and PETO Tunde. “Promising artificial intelligence-machine learning-deep learning algorithms in ophthalmology”. The Asia-Pacific Journal of Ophthalmology 8.3 (2019): 264-272.
9. BOURCIER Tristan., et al. “Robot-assisted simulated cataract surgery”. Journal of Cataract and Refractive Surgery 43.4 (2017): 552-557.
10. SIDDIQUI Aazim A., et al. “Artificial intelligence in cornea, refractive, and cataract surgery”. Current Opinion in Ophthalmology 31.4 (2020): 253-260.
11. RAMPAT Radhika., et al. “Artificial intelligence in cornea, refractive surgery, and cataract: basic principles, clinical applications, and future directions”. Asia-Pacific Journal of Ophthalmology (Philadelphia, Pa.) 10.3 (2021): 268.
12. MISHRA Kapil and LENG Theodore. “Artificial intelligence and ophthalmic surgery”. Current Opinion in Ophthalmology 32.5 (2021): 425-430.
13. BENET David., et al. “Artificial intelligence: the unstoppable revolution in ophthalmology”. Survey of Ophthalmology 67.1 (2022): 252-270.
14. AL-ASWAD Lama A., et al. “Artificial Intelligence for Glaucoma: Creating and Implementing Artificial Intelligence for Disease Detection and Progression”. Ophthalmology Glaucoma (2022).
15. SCHUMAN Joel S., et al. “A Case for the Use of Artificial Intelligence in Glaucoma Assessment”. Ophthalmology Glaucoma 5.3 (2022): e3-e13.
16. COAN Lauren., et al. “Automatic detection of glaucoma via fundus imaging and artificial intelligence: A review”. Survey of Ophthalmology 68.1 (2022): 17-41.
17. BUNOD R., et al. “Artificial intelligence and glaucoma: A literature review”. Journal Francais D'ophtalmologie (2022).
18. TRINH Minh., et al. “Artificial Intelligence in Retina”. Advances in Ophthalmology and Optometry 6 (2021): 175-185.
19. GARGEYA Rishab and LENG Theodore. “Automated identification of diabetic retinopathy using deep learning”. Ophthalmology 124.7 (2017): 962-969.
20. MORARU Andreea Dana., et al. “Artificial intelligence and deep learning in ophthalmology-present and future”. Experimental and Therapeutic Medicine 20.4 (2020): 3469-3473.
21. SORRENTINO Francesco S., et al. “Application of artificial intelligence in targeting retinal diseases”. Current Drug Targets 21.12 (2020): 1208-1215.
22. ATTIKU Yamini., et al. “Current status and future possibilities of retinal imaging in diabetic retinopathy care applicable to low-and medium-income countries”. Indian Journal of Ophthalmology 69.11.20 (2021): 2968.
23. LINDEGGER Daniel Josef., et al. “Evolution and Applications of Artificial Intelligence to Cataract Surgery”. Ophthalmology Science 2.3 (2022).
24. TOGNETTO Daniele., et al. “Artificial intelligence applications and cataract management: A systematic review”. Survey of Ophthalmology (2021).
25. TAHVILDARI., et al. “Application of artificial intelligence in the diagnosis and management of corneal diseases. In: Seminars in Ophthalmology”. Taylor and Francis (2021): 641-648.
26. LUCENA Abrahão Rocha., et al. “Development of an application for providing corneal topography reports based on artificial intelligence”. Arquivos Brasileiros de Oftalmologia 85 (2021): 351-358.
27. LI Zhongwen., et al. “Comparison of deep learning systems and cornea specialists in detecting corneal diseases from low-quality images”. iScience 24.11 (2021): 103317.

Citation

Citation: Ana Clara Coelho Caetano., et al. “Ophthalmology and the Benefits of Using Artificial Intelligence: A Literature Review".Acta Scientific Nutritional Health 7.7 (2023): 66-71.

Copyright

Copyright: © 2023 Ana Clara Coelho Caetano., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.