Utilizing human intelligence in artificial intelligence for detecting glaucomatous fundus images using human-in-the-loop machine learning

Purpose: For diagnosing glaucomatous damage, we have employed a novel convolutional neural network (CNN) from TrueColor confocal fundus images to conquer the black box dilemma in artificial intelligence (AI). This neural network with CNN architecture with human-in-the-loop (HITL) data annotation hel...

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Библиографические подробности

Главные авторы:	Prasanna Venkatesh Ramesh, TamilselvanSubramaniam, PrajnyaRay, Aji Kunnath Devadas, Shruthy Vaishali Ramesh, Sheik Mohamed Ansar, Meena Kumari Ramesh, RameshRajasekaran, SathyanParthasarathi
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Wolters Kluwer Medknow Publications 2022-01-01
Серии:	Indian Journal of Ophthalmology
Предметы:	artificial intelligence confocal fundus images glaucomatous cupping hitl machine learning
Online-ссылка:	http://www.ijo.in/article.asp?issn=0301-4738;year=2022;volume=70;issue=4;spage=1131;epage=1138;aulast=Ramesh
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