AIMC Topic: Visual Fields

Clear Filters Showing 11 to 20 of 120 articles

Macular patterns of neuronal and visual field loss in recovered optic neuritis identified by machine learning.

Scientific reports Dec 28, 2024
We used machine learning to investigate the residual visual field (VF) deficits and macula retinal ganglion cell (RGC) thickness loss patterns in recovered optic neuritis (ON). We applied archetypal analysis (AA) to 377 same-day pairings of 10-2 VF a...
Middle Aged Humans Tomography, Optical Coherence Machine Learning Retinal Ganglion Cells Female Visual Fields Adult Macula Lutea Male Optic Neuritis
View on PubMed DOI

Detection of glaucoma progression on longitudinal series of en-face macular optical coherence tomography angiography images with a deep learning model.

The British journal of ophthalmology Nov 22, 2024
BACKGROUND/AIMS: To design a deep learning (DL) model for the detection of glaucoma progression with a longitudinal series of macular optical coherence tomography angiography (OCTA) images.
Visual Fields Visual Field Tests Fluorescein Angiography Macula Lutea Retinal Vessels Glaucoma, Open-Angle ROC Curve Follow-Up Studies Tomography, Optical Coherence Optic Disk Retinal Ganglion Cells Humans Aged Retrospective Studies Intraocular Pressure Female Male Middle Aged Disease Progression Deep Learning
View on PubMed DOI

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...
Humans Artificial Intelligence Prospective Studies Biomarkers Female Photoreceptor Cells, Vertebrate Geographic Atrophy Visual Acuity Tomography, Optical Coherence Visual Fields Visual Field Tests Retinal Pigment Epithelium Reproducibility of Results Aged Aged, 80 and over Male Middle Aged
View on PubMed DOI

Diagnostic Performance of the Offline Medios Artificial Intelligence for Glaucoma Detection in a Rural Tele-Ophthalmology Setting.

Ophthalmology. Glaucoma Sep 12, 2024
PURPOSE: This study assesses the diagnostic efficacy of offline Medios Artificial Intelligence (AI) glaucoma software in a primary eye care setting, using nonmydriatic fundus images from Remidio's Fundus-on-Phone (FOP NM-10). Artificial intelligence ...
Prospective Studies Female Aged Cross-Sectional Studies Intraocular Pressure Male Humans Glaucoma Artificial Intelligence Visual Fields Middle Aged Rural Population Visual Acuity Ophthalmology Telemedicine
View on PubMed DOI

Identifying Factors Associated With Fast Visual Field Progression in Patients With Ocular Hypertension Based on Unsupervised Machine Learning.

Journal of glaucoma Aug 5, 2024
PRCIS: We developed unsupervised machine learning models to identify different subtypes of patients with ocular hypertension in terms of visual field (VF) progression and discovered 4 subtypes with different trends of VF worsening. We then identified...
Glaucoma, Open-Angle Ocular Hypertension Aged Cross-Sectional Studies Intraocular Pressure Male Middle Aged Disease Progression Follow-Up Studies Unsupervised Machine Learning Vision Disorders Visual Fields Visual Field Tests Humans Female Risk Factors
View on PubMed DOI

Prediction of visual field progression with serial optic disc photographs using deep learning.

The British journal of ophthalmology Jul 23, 2024
AIM: We tested the hypothesis that visual field (VF) progression can be predicted with a deep learning model based on longitudinal pairs of optic disc photographs (ODP) acquired at earlier time points during follow-up.
Optic Nerve Diseases Photography Follow-Up Studies Humans Vision Disorders Glaucoma Intraocular Pressure Optic Disk Retrospective Studies Male Visual Fields Female Middle Aged Visual Field Tests Aged Disease Progression Deep Learning ROC Curve
View on PubMed DOI

Deep-learning-based prediction of glaucoma conversion in normotensive glaucoma suspects.

The British journal of ophthalmology Jun 20, 2024
BACKGROUND/AIMS: To assess the performance of deep-learning (DL) models for prediction of conversion to normal-tension glaucoma (NTG) in normotensive glaucoma suspect (GS) patients.
Humans Algorithms Retrospective Studies Female Aged Intraocular Pressure Male Middle Aged Disease Progression Optic Disk Retinal Ganglion Cells Visual Fields Deep Learning Ocular Hypertension ROC Curve Tonometry, Ocular Follow-Up Studies Low Tension Glaucoma Blood Pressure Nerve Fibers
View on PubMed DOI

Estimating receptive fields of simple and complex cells in early visual cortex: A convolutional neural network model with parameterized rectification.

PLoS computational biology May 31, 2024
Neurons in the primary visual cortex respond selectively to simple features of visual stimuli, such as orientation and spatial frequency. Simple cells, which have phase-sensitive responses, can be modeled by a single receptive field filter in a linea...
Models, Neurological Visual Cortex Neural Networks, Computer Neurons Primary Visual Cortex Animals Visual Fields Computational Biology Cats Photic Stimulation
View on PubMed DOI

Progression or Aging? A Deep Learning Approach for Distinguishing Glaucoma Progression From Age-Related Changes in OCT Scans.

American journal of ophthalmology May 3, 2024
PURPOSE: To develop deep learning (DL) algorithm to detect glaucoma progression using optical coherence tomography (OCT) images, in the absence of a reference standard.
Algorithms Optic Nerve Diseases Glaucoma, Open-Angle Retrospective Studies Humans Female Tomography, Optical Coherence Neural Networks, Computer Aged Nerve Fibers Glaucoma Intraocular Pressure Optic Disk Aging Male Retinal Ganglion Cells Middle Aged Visual Fields Disease Progression Deep Learning Follow-Up Studies
View on PubMed DOI

Prediction of Visual Field Progression with Baseline and Longitudinal Structural Measurements Using Deep Learning.

American journal of ophthalmology Feb 12, 2024
PURPOSE: Identifying glaucoma patients at high risk of progression based on widely available structural data is an unmet task in clinical practice. We test the hypothesis that baseline or serial structural measures can predict visual field (VF) progr...
Optic Nerve Diseases Glaucoma, Open-Angle Aged Humans Intraocular Pressure Tomography, Optical Coherence Deep Learning Glaucoma Male Nerve Fibers Algorithms ROC Curve Middle Aged Optic Disk Retrospective Studies Follow-Up Studies Disease Progression Retinal Ganglion Cells Female Vision Disorders Visual Fields Area Under Curve Visual Field Tests
View on PubMed DOI
Popular Topics
Recent Journals