Nascent geographic atrophy
3 papers study it3 more mention it1 finding
- Humans2
- In silico1
Associations
1Deep learning
upin silico1
1 study
Deep learning
upin silico1
Deep learning predicts nascent geographic atrophy in silico (sensitivity 0.97 (95% CI 0.93-1.00)).
“The AI-assisted approach (utilizing outputs from the deep learning model to guide manual review) had a sensitivity of 0.97 (95% confidence interval [CI] = 0.93-1.00)”
In silicoacross all visits
Ophthalmology science
Latest
Ophthalmology Science
Deep Learning Approaches for Detecting of Nascent Geographic Atrophy in Age-Related Macular Degeneration
Computational studyAge-related macular degeneration
Ophthalmology Science
Targeted High-Density Microperimetry Testing of Nascent Geographic Atrophy in Age-Related Macular Degeneration
Cohort study of 176 peopleAge-related macular degeneration
Clinical & Experimental Ophthalmology
Choroidal signal hypertransmission on optical coherence tomography imaging: Association with development of geographic atrophy in age-related macular degeneration
Cohort study of 140 peopleAge-related macular degeneration
Ophthalmology Retina
OCT Prognostic Biomarkers for Progression to Late Age-related Macular Degeneration: A Systematic Review and Meta-analysis
Meta-analysis of observational studiesAge-related macular degeneration
Ophthalmology Retina
Prospective Longitudinal Evaluation of Nascent Geographic Atrophy in Age-Related Macular Degeneration
Study in peopleBiomarkers