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Artificial intelligence in ophthalmology
One of the fields of medicine in which artificial intelligence techniques have made progress is ophthalmology. Artificial intelligence (A.I.) applications for preventing vision loss in eye illnesses have developed quickly. Artificial intelligence uses computer programs to execute various activities...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Romanian Society of Ophthalmology
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10591433/ https://www.ncbi.nlm.nih.gov/pubmed/37876505 http://dx.doi.org/10.22336/rjo.2023.37 |
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author | Popescu (Patoni), Stella Ioana Muşat, Alexandra Andreea Mihaela Patoni, Cristina Popescu, Marius-Nicolae Munteanu, Mihnea Costache, Ioana Bianca Pîrvulescu, Ruxandra Angela Mușat, Ovidiu |
author_facet | Popescu (Patoni), Stella Ioana Muşat, Alexandra Andreea Mihaela Patoni, Cristina Popescu, Marius-Nicolae Munteanu, Mihnea Costache, Ioana Bianca Pîrvulescu, Ruxandra Angela Mușat, Ovidiu |
author_sort | Popescu (Patoni), Stella Ioana |
collection | PubMed |
description | One of the fields of medicine in which artificial intelligence techniques have made progress is ophthalmology. Artificial intelligence (A.I.) applications for preventing vision loss in eye illnesses have developed quickly. Artificial intelligence uses computer programs to execute various activities while mimicking human thought. Machine learning techniques are frequently utilized in the field of ophthalmology. Ophthalmology holds great promise for advancing artificial intelligence, thanks to various digital methods like optical coherence tomography (OCT) and visual field testing. Artificial intelligence has been used in ophthalmology to treat eye conditions impairing vision, including macular holes (M.H.), age-related macular degeneration (AMD), diabetic retinopathy, glaucoma, and cataracts. The more common occurrence of these diseases has led to artificial intelligence development. It is important to get annual screenings to detect eye diseases such as glaucoma, diabetic retinopathy, and age-related macular degeneration. These conditions can cause decreased visual acuity, and it is necessary to identify any changes or progression in the disease to receive appropriate treatment. Numerous studies have been conducted based on artificial intelligence using different algorithms to improve and simplify current medical practice and for early detection of eye diseases to prevent vision loss. Abbreviations: AI = artificial intelligence, AMD = age-related macular degeneration, ANN = artificial neural networks, AAO = American Academy of Ophthalmology, CNN = convolutional neural network, DL = deep learning, DVP = deep vascular plexus, FDA = Food and Drug Administration, GCL = ganglion cell layer, IDP = Iowa Detection Program, ML = Machine learning techniques, MH = macular holes, MTANN = massive training of the artificial neural network, NLP = natural language processing methods, OCT = optical coherence tomography, RBS = Radial Basis Function, RNFL = nerve fiber layer, ROP = Retinopathy of Prematurity, SAP = standard automated perimetry, SVP = Superficial vascular plexus, U.S. = United States, VEGF = vascular endothelial growth factor |
format | Online Article Text |
id | pubmed-10591433 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Romanian Society of Ophthalmology |
record_format | MEDLINE/PubMed |
spelling | pubmed-105914332023-10-24 Artificial intelligence in ophthalmology Popescu (Patoni), Stella Ioana Muşat, Alexandra Andreea Mihaela Patoni, Cristina Popescu, Marius-Nicolae Munteanu, Mihnea Costache, Ioana Bianca Pîrvulescu, Ruxandra Angela Mușat, Ovidiu Rom J Ophthalmol Reviews One of the fields of medicine in which artificial intelligence techniques have made progress is ophthalmology. Artificial intelligence (A.I.) applications for preventing vision loss in eye illnesses have developed quickly. Artificial intelligence uses computer programs to execute various activities while mimicking human thought. Machine learning techniques are frequently utilized in the field of ophthalmology. Ophthalmology holds great promise for advancing artificial intelligence, thanks to various digital methods like optical coherence tomography (OCT) and visual field testing. Artificial intelligence has been used in ophthalmology to treat eye conditions impairing vision, including macular holes (M.H.), age-related macular degeneration (AMD), diabetic retinopathy, glaucoma, and cataracts. The more common occurrence of these diseases has led to artificial intelligence development. It is important to get annual screenings to detect eye diseases such as glaucoma, diabetic retinopathy, and age-related macular degeneration. These conditions can cause decreased visual acuity, and it is necessary to identify any changes or progression in the disease to receive appropriate treatment. Numerous studies have been conducted based on artificial intelligence using different algorithms to improve and simplify current medical practice and for early detection of eye diseases to prevent vision loss. Abbreviations: AI = artificial intelligence, AMD = age-related macular degeneration, ANN = artificial neural networks, AAO = American Academy of Ophthalmology, CNN = convolutional neural network, DL = deep learning, DVP = deep vascular plexus, FDA = Food and Drug Administration, GCL = ganglion cell layer, IDP = Iowa Detection Program, ML = Machine learning techniques, MH = macular holes, MTANN = massive training of the artificial neural network, NLP = natural language processing methods, OCT = optical coherence tomography, RBS = Radial Basis Function, RNFL = nerve fiber layer, ROP = Retinopathy of Prematurity, SAP = standard automated perimetry, SVP = Superficial vascular plexus, U.S. = United States, VEGF = vascular endothelial growth factor Romanian Society of Ophthalmology 2023 /pmc/articles/PMC10591433/ /pubmed/37876505 http://dx.doi.org/10.22336/rjo.2023.37 Text en #x00A9; The Authors.Romanian Society of Ophthalmology https://creativecommons.org/licenses/by/2.0/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 work is properly cited. |
spellingShingle | Reviews Popescu (Patoni), Stella Ioana Muşat, Alexandra Andreea Mihaela Patoni, Cristina Popescu, Marius-Nicolae Munteanu, Mihnea Costache, Ioana Bianca Pîrvulescu, Ruxandra Angela Mușat, Ovidiu Artificial intelligence in ophthalmology |
title | Artificial intelligence in ophthalmology
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title_full | Artificial intelligence in ophthalmology
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title_fullStr | Artificial intelligence in ophthalmology
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title_full_unstemmed | Artificial intelligence in ophthalmology
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title_short | Artificial intelligence in ophthalmology
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title_sort | artificial intelligence in ophthalmology |
topic | Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10591433/ https://www.ncbi.nlm.nih.gov/pubmed/37876505 http://dx.doi.org/10.22336/rjo.2023.37 |
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