Keywords
Doenças Oculares;
Diagnóstico
Prognóstico
How to Cite
Abstract
This article reviews current literature on the effectiveness of artificial intelligence (AI) in the diagnosis and prognosis of ocular diseases. Article selection was conducted using the PubMed database and the terms “Artificial Intelligence,” “Ocular Diseases,” “Diagnosis,” and “Prognosis.” The review covers recent studies investigating deep learning algorithms, ocular biomarkers, liquid biopsies, and implantable bioelectronic devices for ophthalmic conditions, including diabetic retinopathy, glaucoma, and macular degeneration. The findings indicate that adopting these AI technologies and innovative biomarkers can significantly enhance early detection, diagnostic precision, and treatment personalization, leading to improved quality of life for patients with ocular diseases.
References
AHMAD, B. U.; KIM, J. E.; RAHIMY, E. Fundamentals of artificial intelligence for ophthalmologists. Current Opinion in Ophthalmology, v. 31, n. 5, p. 303-311, 2020.
ABU-AMER, M.; ALTAIRY, M.; BOURA, B. Deep learning-based frameworks for glaucoma detection: A review. Ophthalmology, v. 130, n. 5, p. 623-630, 2021.
BIOUSSE, V.; DANESH-MEYER, H. V.; SAINDANE, A. M.; LAMIREL, C.; NEWMAN, N. J. Imaging of the optic nerve: Technological advances and future prospects. Lancet Neurology, v. 21, n. 12, p. 1135-1150, 2022.
BOURNE, R. R.; KASS, H.; JAMES, A. Application of AI in detecting macular degeneration: A comprehensive review. British Journal of Ophthalmology, v. 105, n. 10, p. 1261-1267, 2021.
DEVALLA, S. K.; LIANG, Z.; PHAM, T. H.; BOOTE, C.; STROUTHIDIS, N. G.; THIERY, A. H.; GIRARD, M. J. A. Glaucoma management in the era of artificial intelligence. British Journal of Ophthalmology, v. 104, n. 3, p. 301-311, 2020.
DU, R.; OHNO-MATSUI, K. Novel uses and challenges of artificial intelligence in diagnosing and managing eyes with high myopia and pathologic myopia. Diagnostics, v. 12, n. 5, p. 1210, 2022.
GURNANI, B.; KAUR, K.; LALGUDI, V. G.; KUNDU, G.; MIMOUNI, M.; LIU, H.; JHANJI, V.; PRAKASH, G.; ROY, A. S.; SHETTY, R.; GURAV, J. S. Role of artificial intelligence, machine learning and deep learning models in corneal disorders - A narrative review. Journal Français d'Ophtalmologie, v. 47, n. 7, p. 104242, 2024.
HÄNER, N. U.; DYSLI, C.; MUNK, M. R. Imaging in retinal vascular disease: A review. Clinical & Experimental Ophthalmology, v. 51, n. 3, p. 217-228, 2023.
KULBAY, M.; MARCOTTE, E.; REMTULLA, R.; LAU, T. H. A.; PAEZ-ESCAMILLA, M.; WU, K. Y.; BURNIER, M. N. JR. Uveal melanoma: Comprehensive review of its pathophysiology, diagnosis, treatment, and future perspectives. Biomedicines, v. 12, n. 8, p. 1758, 2024.
LI, L.; ZHANG, W.; TU, X.; PANG, J.; LAI, I. F.; JIN, C.; CHEUNG, C. Y.; LIN, H. Application of artificial intelligence in precision medicine for diabetic macular edema. Asia-Pacific Journal of Ophthalmology (Philadelphia), v. 12, n. 5, p. 486-494, 2023.
LIU, Y. H.; LI, L. Y.; LIU, S. J.; GAO, L. X.; TANG, Y.; LI, Z. H.; YE, Z. Artificial intelligence in the anterior segment of eye diseases. International Journal of Ophthalmology, v. 17, n. 9, p. 1743-1751, 2024.
LIMA, R. V.; ARRUDA, M. P.; MUNIZ, M. C. R.; FILHO, H. N. F.; FERREIRA, D. M. R.; PEREIRA, S. M. Artificial intelligence methods in diagnosis of retinoblastoma based on fundus imaging: A systematic review and meta-analysis. Graefe’s Archive for Clinical and Experimental Ophthalmology, 2024.
PUCCIO, A.; KRANCE, S. H.; PUR, D. R.; BHATTI, J.; BASSI, A.; MANICHAVAGAN, K.; BRAHMBHATT, S.; AGGARWAL, I.; SINGH, P.; VIRANI, A.; STANLEY, M.; MIRANDA, R. N.; FELFELI, T. Applications of artificial intelligence and bioinformatics methodologies in the analysis of ocular biofluid markers: A scoping review. Graefe’s Archive for Clinical and Experimental Ophthalmology, v. 262, n. 4, p. 1041-1091, 2024.
ROCKSMITH, E. R.; REDING, M. J. New developments in stroke rehabilitation. Current Atherosclerosis Reports, v. 4, n. 4, p. 277-284, 2002.
SCHMIDT-ERFURTH, U.; SADEGHIPOUR, A.; GERENDAS, B. S.; WALDSTEIN, S. M.; BOGUNOVIC, H. Artificial intelligence in retina. Progress in Retinal and Eye Research, v. 67, p. 1-29, 2018.
TONTI, E.; TONTI, S.; MANCINI, F.; BONINI, C.; SPADEA, L.; D'ESPOSITO, F.; GAGLIANO, C.; MUSA, M.; ZEPPIERI, M. Artificial intelligence and advanced technology in glaucoma: A review. Journal of Personalized Medicine, v. 14, n. 10, p. 1062, 2024.
VERBEEK, S.; DALVIN, L. A. Advances in multimodal imaging for diagnosis of pigmented ocular fundus lesions. Canadian Journal of Ophthalmology, v. 59, n. 4, p. 218-233, 2024.
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Copyright (c) 2024 Breno Mangueira Dantas, Vasques Vinícius de França Landim Parente, Samuel Décio Azevedo dos Santos, Luiz Gonzaga Júnior, Walmo Santana de Medeiros Neto, Marina Gomes Carlos, Ruan Pablo da Costa Araújo, Fernanda Yohanna Gonçalves Bezerra, Natan Reis Brito, Maria Klara Waldmann, Rennan Fael Lucena Bispo, Érico Bezerra Florencio Ferreira, Mylena Thuannya Paiva Silva Medeiros, Thiciano Sacramento Aragão, Mirelly Jayne Cavalcante Cruz, Anna Karen de Oliveira Moreira, Pedro Lucas Loiola Guedes Noronha, Hiago Vitório Castro Lima de Melo, Kleber Vinicius Rodrigues de Vasconcelos, Lucas Machado Medeiros, Samuel Maia Lira