ArticleJournal of the Royal Society, Interface2015
Patterns of functional vision loss in glaucoma determined with archetypal analysis.
Article in Journal of the Royal Society, Interface, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers.
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The trial behind it
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Who cites it
81 citing papers in PubMed, 126 citations in OpenAlex.
- Unsupervised Classification of Wide-Field Swept-Source Optical Coherence Tomography Reveals Patterns Associated With Glaucoma Severity and Progression.Translational vision science & technology · 2026Article
- Comparing the Use of Measured and Smoothed Data in Forecasting Visual Field Tests Using Deep Learning.Ophthalmology science · 2026Article
- Spatial Decomposition of Longitudinal RNFL Maps Reveals Distinct Modes of Glaucomatous Progression With Structure-Function and Genetic Signatures.Investigative ophthalmology & visual science · 2026Article
- Unsupervised Clustering for POAG Phenotyping.Investigative ophthalmology & visual science · 2026Article
- Archetypal Visual Field Analysis of Patients With Chronic Leber Hereditary Optic Neuropathy in Relation to Visual Recovery.Investigative ophthalmology & visual science · 2026Article
- Devising and Evaluating an Adaptive Static-Automated Perimetry Test for Children: A Feasibility Study.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2026Article
- Archetypes of Binocular Visual Field Loss and Their Impact on Vision-Related Quality of Life in Glaucoma Patients.Investigative ophthalmology & visual science · 2026Article
- Reliable and Interpretable Visual Field Progression Prediction with Diffusion Models and Conformal Risk Control.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2026Article
- Dual-Level Pattern Tree for Visual Field Improves Glaucoma Progression and Polygenic Risk Prediction.Translational vision science & technology · 2025Article
- Connecting Visual Perception With Proton Therapy-Induced Optic Damage Using Archetypal Analysis.International journal of particle therapy · 2025Article
- Archetypal Analysis Reveals Consistent Visual Field Patterns for Stimulus Size III and Size Modulation Perimetry in Glaucoma.Translational vision science & technology · 2025Article
- Optic Nerve Atrophy Conditions Associated With 3D Unsegmented Optical Coherence Tomography Volumes Using Deep Learning.JAMA ophthalmology · 2025Article
- Genetic Risk for Open-Angle Glaucoma Subtypes Is Associated with Specific Visual Field Defect Classes.Ophthalmology · 2025Article
- Enhancing central visual field loss representation with a hybrid unsupervised approach.International ophthalmology · 2025Article
- Machine Learning Applied to Visual Fields of Dominant Optic Atrophy Patients.Translational vision science & technology · 2025Article
- PyGlaucoMetrics: A Stacked Weight-Based Machine Learning Approach for Glaucoma Detection Using Visual Field Data.Medicina (Kaunas, Lithuania) · 2025Article
- Democratizing Glaucoma Care: A Framework for AI-Driven Progression Prediction Across Diverse Healthcare Settings.Journal of ophthalmology · 2025Article
- Macular patterns of neuronal and visual field loss in recovered optic neuritis identified by machine learning.Scientific reports · 2024Article
- Archetypal Analysis Reveals Consistent Visual Field Patterns for Stimulus Sizes III and V in Glaucoma and NAION.Translational vision science & technology · 2024Article
- Novel Approaches for the Early Detection of Glaucoma Using Artificial Intelligence.Life (Basel, Switzerland) · 2024Review
21 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
Abstract
Glaucoma is an optic neuropathy accompanied by vision loss which can be mapped by visual field (VF) testing revealing characteristic patterns related to the retinal nerve fibre layer anatomy. While detailed knowledge about these patterns is important to understand the anatomic and genetic aspects of glaucoma, current classification schemes are typically predominantly derived qualitatively. Here, we classify glaucomatous vision loss quantitatively by statistically learning prototypical patterns on the convex hull of the data space. In contrast to component-based approaches, this method emphasizes distinct aspects of the data and provides patterns that are easier to interpret for clinicians. Based on 13 231 reliable Humphrey VFs from a large clinical glaucoma practice, we identify an optimal solution with 17 glaucomatous vision loss prototypes which fit well with previously described qualitative patterns from a large clinical study. We illustrate relations of our patterns to retinal structure by a previously developed mathematical model. In contrast to the qualitative clinical approaches, our results can serve as a framework to quantify the various subtypes of glaucomatous visual field loss.
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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.