Development and validation of an automated machine learning model for the multi-class classification of diabetic retinopathy, central retinal vein occlusion and branch retinal vein occlusion based on color fundus photographs

Introduction: Automated machine learning (AutoML) is a novel artificial intelligence (AI) strategy that enables clinicians without coding experience to develop their own AI models. This study assessed the discriminative performance of AutoML in differentiating diabetic retinopathy (DR), central reti...

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Auteurs principaux:	Carolyn Yu Tung Wong, Timing Liu, Tin Lik Wong, Justin Man Kit Tong, Henry Hing Wai Lau, Pearse Andrew Keane
Format:	Artigo
Langue:	Inglês
Publié:	Elsevier 2024-09-01
Collection:	JFO Open Ophthalmology
Sujets:	Automated machine learning Artificial intelligence Diabetic retinopathy Central retinal vein occlusion Branch retinal vein occlusion
Accès en ligne:	http://www.sciencedirect.com/science/article/pii/S2949889924000412
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