AI Medical Compendium Topic

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Epiretinal Membrane

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Comparison between support vector machine and deep learning, machine-learning technologies for detecting epiretinal membrane using 3D-OCT.

International ophthalmology
PURPOSE: In this study, we compared deep learning (DL) with support vector machine (SVM), both of which use three-dimensional optical coherence tomography (3D-OCT) images for detecting epiretinal membrane (ERM).

Artificial intelligence-based detection of epimacular membrane from color fundus photographs.

Scientific reports
Epiretinal membrane (ERM) is a common ophthalmological disorder of high prevalence. Its symptoms include metamorphopsia, blurred vision, and decreased visual acuity. Early diagnosis and timely treatment of ERM is crucial to preventing vision loss. Al...

DEEP LEARNING-BASED PREDICTION OF OUTCOMES FOLLOWING NONCOMPLICATED EPIRETINAL MEMBRANE SURGERY.

Retina (Philadelphia, Pa.)
PURPOSE: We used deep learning to predict the final central foveal thickness (CFT), changes in CFT, final best corrected visual acuity, and best corrected visual acuity changes following noncomplicated idiopathic epiretinal membrane surgery.

Automated Detection of Epiretinal Membranes in OCT Images Using Deep Learning.

Ophthalmic research
INTRODUCTION: Development and validation of a deep learning algorithm to automatically identify and locate epiretinal memberane (ERM) regions in OCT images.