ReviewActa ophthalmologica2023
Multimodal imaging and deep learning in geographic atrophy secondary to age-related macular degeneration.
Review in Acta ophthalmologica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06536062 (Age-related Macular Degeneration of Atrophic Type Treated With Intravitreal Injection of Umbilical Cord Blood Enriched With Platelet Plasma), which is not on this map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Age-related Macular Degeneration of Atrophic Type Treated With Intravitreal Injection of Umbilical Cord Blood Enriched With Platelet Plasma: Multicenter Study.
Who cites it
10 citing papers in PubMed, 12 citations in OpenAlex.
- Incomplete Retinal Pigment Epithelium and Outer Retinal Atrophy Characterized Using Fundus Autofluorescence: An 18-Month Post Hoc Analysis of GATHER2.Investigative ophthalmology & visual science · 2026Trial
- The optical coherence tomography and microperimetry biomarker evaluation in patients with geographic atrophy (OMEGA) study: Geographic atrophy progression in fundus autofluorescence - OMEGA report 3.Acta ophthalmologica · 2026Article
- Exploratory study on a novel automatic quantification software by artificial intelligence for geographic atrophy associated to age-related macular degeneration.International journal of retina and vitreous · 2026Article
- Reinforcement-based leveraging transfer learning for multiclass optical coherence tomography images classification.Scientific reports · 2025Article
- Deep Learning Approaches to Predict Geographic Atrophy Progression Using Three-Dimensional OCT Imaging.Translational vision science & technology · 2025Article
- Global trends and hotspots in artificial intelligence for high myopia: a bibliometric analysis.Frontiers in medicine · 2025Article
- [Use of artificial intelligence for recognition of biomarkers in intermediate age-related macular degeneration].Die Ophthalmologie · 2024Review
- [Use of artificial intelligence in geographic atrophy in age-related macular degeneration].Die Ophthalmologie · 2024Review
- Compare three deep learning-based artificial intelligence models for classification of calcified lumbar disc herniation: a multicenter diagnostic study.Frontiers in surgery · 2024Article
- Innovative technologies for the treatment of dry age-related macular degeneration (AMD) - modern therapeutic perspectives and their future.Romanian journal of ophthalmologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
Abstract
Geographic atrophy (GA) secondary to age-related macular degeneration is among the most common causes of irreversible vision loss in industrialized countries. Recently, two therapies have been approved by the US FDA. However, given the nature of their treatment effect, which primarily involves a relative decrease in disease progression, discerning the individual treatment response at the individual level may not be readily apparent. Thus, clinical decision-making may have to rely on the quantification of the slope of GA progression before and during treatment. A panel of imaging modalities and artificial intelligence (AI)-based algorithms are available for such quantifications. This article aims to provide a comprehensive overview of the fundamentals of GA imaging, the procedures for diagnosis and classification using these images, and the cutting-edge role of AI algorithms in automatically deriving diagnostic and prognostic insights from imaging data.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.