AIMC Topic: Geographic Atrophy
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Repeatability of Microperimetry in Areas of Retinal Pigment Epithelium and Photoreceptor Loss in Geographic Atrophy Supported by Artificial Intelligence-Based Optical Coherence Tomography Biomarker Quantification.
American journal of ophthalmology
Nov 14, 2024
PURPOSE: Growing interest in microperimetry (MP) or fundus-controlled perimetry as a targeted psychometric testing method in geographic atrophy (GA) is warranted because of the disease subclinical/extrafoveal appearance or preexisting foveal loss wit...
A Novel Management Challenge in Age-Related Macular Degeneration: Artificial Intelligence and Expert Prediction of Geographic Atrophy.
Ophthalmology. Retina
Nov 9, 2024
PURPOSE: The progression of geographic atrophy (GA) secondary to age-related macular degeneration is highly variable among individuals. Prediction of the progression is critical to identify patients who will benefit most from the first treatments cur...
Disease Progression
Deep Learning
Follow-Up Studies
Aged, 80 and over
Male
Middle Aged
Macular Degeneration
Humans
Disease Management
Artificial Intelligence
Visual Acuity
Prospective Studies
Algorithms
Fluorescein Angiography
Tomography, Optical Coherence
Female
Geographic Atrophy
Fundus Oculi
Aged
AI in the clinical management of GA: A novel therapeutic universe requires novel tools.
Progress in retinal and eye research
Sep 27, 2024
Regulatory approval of the first two therapeutic substances for the management of geographic atrophy (GA) secondary to age-related macular degeneration (AMD) is a major breakthrough following failure of numerous previous trials. However, in the absen...
Artificial intelligence for geographic atrophy: pearls and pitfalls.
Current opinion in ophthalmology
Sep 9, 2024
PURPOSE OF REVIEW: This review aims to address the recent advances of artificial intelligence (AI) in the context of clinical management of geographic atrophy (GA), a vision-impairing late-stage manifestation of age-related macular degeneration (AMD)...
Disease Activity and Therapeutic Response to Pegcetacoplan for Geographic Atrophy Identified by Deep Learning-Based Analysis of OCT.
Ophthalmology
Aug 14, 2024
PURPOSE: To quantify morphological changes of the photoreceptors (PRs) and retinal pigment epithelium (RPE) layers under pegcetacoplan therapy in geographic atrophy (GA) using deep learning-based analysis of OCT images.
[Use of artificial intelligence in geographic atrophy in age-related macular degeneration].
Die Ophthalmologie
Jul 31, 2024
The first regulatory approval of treatment for geographic atrophy (GA) secondary to age-related macular degeneration in the USA constitutes an important milestone; however, due to the nature of GA as a non-acute, insidiously progressing pathology, th...
Deep-learning automated quantification of longitudinal OCT scans demonstrates reduced RPE loss rate, preservation of intact macular area and predictive value of isolated photoreceptor degeneration in geographic atrophy patients receiving C3 inhibition treatment.
The British journal of ophthalmology
Mar 20, 2024
OBJECTIVE: To evaluate the role of automated optical coherence tomography (OCT) segmentation, using a validated deep-learning model, for assessing the effect of C3 inhibition on the area of geographic atrophy (GA); the constituent features of GA on O...
Explainable artificial intelligence model for the detection of geographic atrophy using colour retinal photographs.
BMJ open ophthalmology
Dec 6, 2023
OBJECTIVE: To develop and validate an explainable artificial intelligence (AI) model for detecting geographic atrophy (GA) via colour retinal photographs.
Deep learning model for automatic differentiation of EMAP from AMD in macular atrophy.
Scientific reports
Nov 21, 2023
To create a deep learning (DL) classifier pre-trained on fundus autofluorescence (FAF) images that can assist the clinician in distinguishing age-related geographic atrophy from extensive macular atrophy and pseudodrusen-like appearance (EMAP). Patie...
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