Deep Learning for Prediction of AMD Progression: A Pilot Study | Zendy

Daniel B. Russakoff | Zendy; Ali Lamin | Zendy; Jonathan D. Oakley | Zendy; Adam M. Dubis | Zendy; Sobha Sivaprasad | Zendy

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Deep Learning for Prediction of AMD Progression: A Pilot Study

Author(s) -

Daniel B. Russakoff,

Ali Lamin,

Jonathan D. Oakley,

Adam M. Dubis,

Sobha Sivaprasad

Publication year - 2019

Publication title -

investigative ophthalmology and visual science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.935

H-Index - 218

eISSN - 1552-5783

pISSN - 0146-0404

DOI - 10.1167/iovs.18-25325

Subject(s) - optical coherence tomography , preprocessor , artificial intelligence , deep learning , segmentation , receiver operating characteristic , convolutional neural network , computer science , pattern recognition (psychology) , macular degeneration , ophthalmology , medicine , machine learning

To develop and assess a method for predicting the likelihood of converting from early/intermediate to advanced wet age-related macular degeneration (AMD) using optical coherence tomography (OCT) imaging and methods of deep learning.

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