2020
DOI: 10.1038/s41591-020-0867-7
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Predicting conversion to wet age-related macular degeneration using deep learning

Abstract: Progression to exudative 'wet' age-related macular degeneration (exAMD) is a major cause of visual deterioration. In patients diagnosed with exAMD in one eye, we introduce an artificial intelligence (AI) system to predict progression to exAMD in the second eye. By combining models based on 3D optical coherence tomography images and corresponding automatic tissue maps, our system predicts conversion to exAMD within a clinically-actionable 6-month time window, achieving a per-volumetric-scan sensitivity of 80% a… Show more

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Cited by 214 publications
(168 citation statements)
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“…14 While AI systems have been researched for some time, recent advances in deep learning and neural networks have gained considerable interest for their potential in health applications. Examples of such applications are wide ranging and include AI systems for screening and triage, 15,16 diag nosis, [17][18][19][20] prognostication, 21,22 decision support, 23 and treat ment recommendation. 24 However, in the most recent cases, published evidence has consisted of in-silico, early-phase validation.…”
Section: Introductionmentioning
confidence: 99%
“…14 While AI systems have been researched for some time, recent advances in deep learning and neural networks have gained considerable interest for their potential in health applications. Examples of such applications are wide ranging and include AI systems for screening and triage, 15,16 diag nosis, [17][18][19][20] prognostication, 21,22 decision support, 23 and treat ment recommendation. 24 However, in the most recent cases, published evidence has consisted of in-silico, early-phase validation.…”
Section: Introductionmentioning
confidence: 99%
“…While AI systems have been researched for some time, recent advances in deep learning and neural networks have gained significant interest for their potential in health applications. Examples of such applications are wide-ranging and include AI systems for screening and triage,1516 diagnosis,17181920prognostication,2122 decision-support23 and treatment recommendation 24. However, in most recent cases, published evidence consists of in silico , early-phase validation.…”
Section: Introductionmentioning
confidence: 99%
“…While AI systems have been researched for some time, recent advances in deep learning and neural networks have gained considerable interest for their potential in health applications. Examples of such applications are wide ranging and include AI systems for screening and triage 15 , 16 , diagnosis 17 20 ,prognostication 21 , 22 , decision support 23 and treatment recommendation 24 . However, in the most recent cases, published evidence has consisted of in silico, early-phase validation.…”
Section: Mainmentioning
confidence: 99%