TY - JOUR
T1 - Assistive applications of artificial intelligence in ophthalmology
AU - Hubbard, Donald C.
AU - Cox, Parker
AU - Redd, Travis K.
N1 - Publisher Copyright:
© 2023 Lippincott Williams and Wilkins. All rights reserved.
PY - 2023/5/1
Y1 - 2023/5/1
N2 - Purpose of reviewAssistive (nonautonomous) artificial intelligence (AI) models designed to support (rather than function independently of) clinicians have received increasing attention in medicine. This review aims to highlight several recent developments in these models over the past year and their ophthalmic implications.Recent findingsArtificial intelligence models with a diverse range of applications in ophthalmology have been reported in the literature over the past year. Many of these systems have reported high performance in detection, classification, prognostication, and/or monitoring of retinal, glaucomatous, anterior segment, and other ocular pathologies.SummaryOver the past year, developments in AI have been made that have implications affecting ophthalmic surgical training and refractive outcomes after cataract surgery, therapeutic monitoring of disease, disease classification, and prognostication. Many of these recently developed models have obtained encouraging results and have the potential to serve as powerful clinical decision-making tools pending further external validation and evaluation of their generalizability.
AB - Purpose of reviewAssistive (nonautonomous) artificial intelligence (AI) models designed to support (rather than function independently of) clinicians have received increasing attention in medicine. This review aims to highlight several recent developments in these models over the past year and their ophthalmic implications.Recent findingsArtificial intelligence models with a diverse range of applications in ophthalmology have been reported in the literature over the past year. Many of these systems have reported high performance in detection, classification, prognostication, and/or monitoring of retinal, glaucomatous, anterior segment, and other ocular pathologies.SummaryOver the past year, developments in AI have been made that have implications affecting ophthalmic surgical training and refractive outcomes after cataract surgery, therapeutic monitoring of disease, disease classification, and prognostication. Many of these recently developed models have obtained encouraging results and have the potential to serve as powerful clinical decision-making tools pending further external validation and evaluation of their generalizability.
KW - artificial intelligence
KW - assistive diagnostics
KW - deep learning
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U2 - 10.1097/ICU.0000000000000939
DO - 10.1097/ICU.0000000000000939
M3 - Review article
C2 - 36728651
AN - SCOPUS:85151361338
SN - 1040-8738
VL - 34
SP - 261
EP - 266
JO - Current opinion in ophthalmology
JF - Current opinion in ophthalmology
IS - 3
ER -