Cross-instrument optical coherence tomography-angiography (OCTA)-based prediction of age-related macular degeneration (AMD) disease activity using artificial intelligence

Cross-instrument optical coherence tomography-angiography (OCTA)-based prediction of age-related macular degeneration (AMD) disease activity using artificial intelligence

Abstract This study investigates the efficacy of predicting age-related macular degeneration (AMD) activity through deep neural networks (DNN) using a cross-instrument training dataset composed of Optical coherence tomography-angiography (OCTA) images from two different manufacturers. A retrospectiv...

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Bibliographic Details
Main Authors: Anna Heinke, Haochen Zhang, Krzysztof Broniarek, Katarzyna Michalska-Małecka, Wyatt Elsner, Carlo Miguel B. Galang, Daniel N. Deussen, Alexandra Warter, Fritz Kalaw, Ines Nagel, Akshay Agnihotri, Nehal N. Mehta, Julian Elias Klaas, Valerie Schmelter, Igor Kozak, Sally L. Baxter, Dirk-Uwe Bartsch, Lingyun Cheng, Cheolhong An, Truong Nguyen, William R. Freeman
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Scientific Reports
Subjects:
Optical coherence tomography-angiography (OCTA)
Cross-instrument training
Artificial intelligence (AI)
Deep neural networks (DNN)
Age-related macular degeneration (AMD)
Online Access:https://doi.org/10.1038/s41598-024-78327-0
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