Longitudinal Validation of the Artificial Intelligence Algorithm in Home OCT for Age-Related Macular

Theodore Leng1, Ella H Leung2, S Krishna Mukkamala2

  • 1Byers Eye Institute at Stanford, Stanford University School of Medicine, Palo Alto, California.

Ophthalmology Science
|January 19, 2026
PubMed
Abstract

Related Concept Videos

Ex Vivo OCT-Based Multimodal Imaging of Human Donor Eyes for Research into Age-Related Macular Degeneration10:14

Ex Vivo OCT-Based Multimodal Imaging of Human Donor Eyes for Research into Age-Related Macular Degeneration

Laboratory assays can leverage prognostic value from the longitudinal optical coherence tomography (OCT)-based multimodal imaging of age-related macular degeneration (AMD). Human donor eyes with and without AMD are imaged using OCT, color, near-infrared reflectance scanning laser ophthalmoscopy, and autofluorescence at two excitation wavelengths prior to tissue...
4.2K
Regenerative Therapy by Suprachoroidal Cell Autograft in Dry Age-related Macular Degeneration: Preliminary In Vivo Report10:24

Regenerative Therapy by Suprachoroidal Cell Autograft in Dry Age-related Macular Degeneration: Preliminary In Vivo Report

The goal of this study is to assess whether the suprachoroidal graft of adipose-derived stem cells included in the stromal vascular fraction and platelets derived from platelet-rich plasma by the Limoli Retinal Restoration Technique can improve visual acuity and retinal sensitivity responses in eyes affected by dry age-related macular...
10.7K
A Workflow to Quantitatively Determine Age-Related Macular Degeneration Lesion-Specific Variations in Fundus Autofluorescence08:54

A Workflow to Quantitatively Determine Age-Related Macular Degeneration Lesion-Specific Variations in Fundus Autofluorescence

This research describes a workflow to determine and compare autofluorescence levels from individual regions of interest (e.g., drusen and subretinal drusenoid deposits in age-related macular degeneration [AMD]) while accounting for varying autofluorescence levels throughout the...
2.1K
Artificial Intelligence-Based System for Detecting Attention Levels in Students06:37

Artificial Intelligence-Based System for Detecting Attention Levels in Students

This paper proposes an artificial intelligence-based system to automatically detect whether students are paying attention to the class or are distracted. This system is designed to help teachers maintain students' attention, optimize their lessons, and dynamically introduce modifications in order for them to be more...
5.3K
Characterization of Vascular Morphology of Neovascular Age-Related Macular Degeneration by Indocyanine Green Angiography05:14

Characterization of Vascular Morphology of Neovascular Age-Related Macular Degeneration by Indocyanine Green Angiography

Currently, fluorescein angiography (FA) is the preferred method for identifying leakage patterns in animal models of choroidal neovascularization (CNV). However, FA does not provide information about vascular morphology. This protocol outlines the use of indocyanine green angiography (ICGA) to characterize different lesion types of laser-induced CNV in mouse...
1.5K
Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Integrated image management, artificial intelligence (AI), and reporting systems have revolutionized diagnostic pathology practice. In this paper, we introduce FlexLIS, a state-of-the-art system that enables AI to assist pathologists in performing histopathology image assessments and generating diagnostic reports.
811