Use of artificial intelligence in ophthalmology: a narrative review
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | São Paulo medical journal (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-31802022000600837 |
Resumo: | ABSTRACT BACKGROUND: Artificial intelligence (AI) deals with development of algorithms that seek to perceive one’s environment and perform actions that maximize one’s chance of successfully reaching one’s predetermined goals. OBJECTIVE: To provide an overview of the basic principles of AI and its main studies in the fields of glaucoma, retinopathy of prematurity, age-related macular degeneration and diabetic retinopathy. From this perspective, the limitations and potential challenges that have accompanied the implementation and development of this new technology within ophthalmology are presented. DESIGN AND SETTING: Narrative review developed by a research group at the Universidade Federal de São Paulo (UNIFESP), São Paulo (SP), Brazil. METHODS: We searched the literature on the main applications of AI within ophthalmology, using the keywords “artificial intelligence”, “diabetic retinopathy”, “macular degeneration age-related”, “glaucoma” and “retinopathy of prematurity,” covering the period from January 1, 2007, to May 3, 2021. We used the MEDLINE database (via PubMed) and the LILACS database (via Virtual Health Library) to identify relevant articles. RESULTS: We retrieved 457 references, of which 47 were considered eligible for intensive review and critical analysis. CONCLUSION: Use of technology, as embodied in AI algorithms, is a way of providing an increasingly accurate service and enhancing scientific research. This forms a source of complement and innovation in relation to the daily skills of ophthalmologists. Thus, AI adds technology to human expertise. |
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Use of artificial intelligence in ophthalmology: a narrative reviewArtificial intelligenceGlaucomaRetinopathy of prematurityOphthalmologyNeural networkConvolutional neural networkDiabetesMacular degenerationDeep reinforcement learningABSTRACT BACKGROUND: Artificial intelligence (AI) deals with development of algorithms that seek to perceive one’s environment and perform actions that maximize one’s chance of successfully reaching one’s predetermined goals. OBJECTIVE: To provide an overview of the basic principles of AI and its main studies in the fields of glaucoma, retinopathy of prematurity, age-related macular degeneration and diabetic retinopathy. From this perspective, the limitations and potential challenges that have accompanied the implementation and development of this new technology within ophthalmology are presented. DESIGN AND SETTING: Narrative review developed by a research group at the Universidade Federal de São Paulo (UNIFESP), São Paulo (SP), Brazil. METHODS: We searched the literature on the main applications of AI within ophthalmology, using the keywords “artificial intelligence”, “diabetic retinopathy”, “macular degeneration age-related”, “glaucoma” and “retinopathy of prematurity,” covering the period from January 1, 2007, to May 3, 2021. We used the MEDLINE database (via PubMed) and the LILACS database (via Virtual Health Library) to identify relevant articles. RESULTS: We retrieved 457 references, of which 47 were considered eligible for intensive review and critical analysis. CONCLUSION: Use of technology, as embodied in AI algorithms, is a way of providing an increasingly accurate service and enhancing scientific research. This forms a source of complement and innovation in relation to the daily skills of ophthalmologists. Thus, AI adds technology to human expertise.Associação Paulista de Medicina - APM2022-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-31802022000600837Sao Paulo Medical Journal v.140 n.6 2022reponame:São Paulo medical journal (Online)instname:Associação Paulista de Medicinainstacron:APM10.1590/1516-3180.2021.0713.r1.22022022info:eu-repo/semantics/openAccessMartins,Thiago Gonçalves dos SantosSchor,PauloMendes,Luís Guilherme ArneiroFowler,SusanSilva,Rufinoeng2022-10-27T00:00:00Zoai:scielo:S1516-31802022000600837Revistahttp://www.scielo.br/spmjhttps://old.scielo.br/oai/scielo-oai.phprevistas@apm.org.br1806-94601516-3180opendoar:2022-10-27T00:00São Paulo medical journal (Online) - Associação Paulista de Medicinafalse |
dc.title.none.fl_str_mv |
Use of artificial intelligence in ophthalmology: a narrative review |
title |
Use of artificial intelligence in ophthalmology: a narrative review |
spellingShingle |
Use of artificial intelligence in ophthalmology: a narrative review Martins,Thiago Gonçalves dos Santos Artificial intelligence Glaucoma Retinopathy of prematurity Ophthalmology Neural network Convolutional neural network Diabetes Macular degeneration Deep reinforcement learning |
title_short |
Use of artificial intelligence in ophthalmology: a narrative review |
title_full |
Use of artificial intelligence in ophthalmology: a narrative review |
title_fullStr |
Use of artificial intelligence in ophthalmology: a narrative review |
title_full_unstemmed |
Use of artificial intelligence in ophthalmology: a narrative review |
title_sort |
Use of artificial intelligence in ophthalmology: a narrative review |
author |
Martins,Thiago Gonçalves dos Santos |
author_facet |
Martins,Thiago Gonçalves dos Santos Schor,Paulo Mendes,Luís Guilherme Arneiro Fowler,Susan Silva,Rufino |
author_role |
author |
author2 |
Schor,Paulo Mendes,Luís Guilherme Arneiro Fowler,Susan Silva,Rufino |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Martins,Thiago Gonçalves dos Santos Schor,Paulo Mendes,Luís Guilherme Arneiro Fowler,Susan Silva,Rufino |
dc.subject.por.fl_str_mv |
Artificial intelligence Glaucoma Retinopathy of prematurity Ophthalmology Neural network Convolutional neural network Diabetes Macular degeneration Deep reinforcement learning |
topic |
Artificial intelligence Glaucoma Retinopathy of prematurity Ophthalmology Neural network Convolutional neural network Diabetes Macular degeneration Deep reinforcement learning |
description |
ABSTRACT BACKGROUND: Artificial intelligence (AI) deals with development of algorithms that seek to perceive one’s environment and perform actions that maximize one’s chance of successfully reaching one’s predetermined goals. OBJECTIVE: To provide an overview of the basic principles of AI and its main studies in the fields of glaucoma, retinopathy of prematurity, age-related macular degeneration and diabetic retinopathy. From this perspective, the limitations and potential challenges that have accompanied the implementation and development of this new technology within ophthalmology are presented. DESIGN AND SETTING: Narrative review developed by a research group at the Universidade Federal de São Paulo (UNIFESP), São Paulo (SP), Brazil. METHODS: We searched the literature on the main applications of AI within ophthalmology, using the keywords “artificial intelligence”, “diabetic retinopathy”, “macular degeneration age-related”, “glaucoma” and “retinopathy of prematurity,” covering the period from January 1, 2007, to May 3, 2021. We used the MEDLINE database (via PubMed) and the LILACS database (via Virtual Health Library) to identify relevant articles. RESULTS: We retrieved 457 references, of which 47 were considered eligible for intensive review and critical analysis. CONCLUSION: Use of technology, as embodied in AI algorithms, is a way of providing an increasingly accurate service and enhancing scientific research. This forms a source of complement and innovation in relation to the daily skills of ophthalmologists. Thus, AI adds technology to human expertise. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-12-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-31802022000600837 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-31802022000600837 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1516-3180.2021.0713.r1.22022022 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Paulista de Medicina - APM |
publisher.none.fl_str_mv |
Associação Paulista de Medicina - APM |
dc.source.none.fl_str_mv |
Sao Paulo Medical Journal v.140 n.6 2022 reponame:São Paulo medical journal (Online) instname:Associação Paulista de Medicina instacron:APM |
instname_str |
Associação Paulista de Medicina |
instacron_str |
APM |
institution |
APM |
reponame_str |
São Paulo medical journal (Online) |
collection |
São Paulo medical journal (Online) |
repository.name.fl_str_mv |
São Paulo medical journal (Online) - Associação Paulista de Medicina |
repository.mail.fl_str_mv |
revistas@apm.org.br |
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1754209269003059200 |