Strong versus Weak Data Labeling for Artificial Intelligence Algorithms in the Measurement of Geographic Atrophy

Strong versus Weak Data Labeling for Artificial Intelligence Algorithms in the Measurement of Geographic Atrophy

Purpose: To gain an understanding of data labeling requirements to train deep learning models for measurement of geographic atrophy (GA) with fundus autofluorescence (FAF) images. Design: Evaluation of artificial intelligence (AI) algorithms. Subjects: The Age-Related Eye Disease Study 2 (AREDS2) im...

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Bibliographic Details
Main Authors: Amitha Domalpally, MD, PhD, Robert Slater, PhD, Rachel E. Linderman, PhD, Rohit Balaji, Jacob Bogost, Rick Voland, PhD, Jeong Pak, PhD, Barbara A. Blodi, MD, Roomasa Channa, MD, Donald Fong, MD, Emily Y. Chew, MD
Format: Article
Language:English
Published: Elsevier 2024-09-01
Series:Ophthalmology Science
Subjects:
Artificial intelligence
Geographic atrophy
Dry AMD
Data labeling
Online Access:http://www.sciencedirect.com/science/article/pii/S2666914524000137

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http://www.sciencedirect.com/science/article/pii/S2666914524000137

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