Back
#1
25.9%
Top 0.7%
13.8%
Top 10%
13.8%
Top 1%
10.9%
Top 61%
9.1%
Top 6%
4.5%
Top 34%
2.5%
Top 26%
1.8%
Top 6%
1.4%
Top 14%
1.1%
Top 65%
0.8%
Top 27%
0.5%
Top 4%
0.5%
Top 7%
0.5%
Top 36%
0.5%
Top 11%
0.5%
Top 8%
0.5%
Multi-class classification of central and non-central geographic atrophy using Optical Coherence Tomography
2025-05-28
ophthalmology
Title + abstract only
View on medRxiv
Show abstract
PurposeTo develop and validate deep learning (DL)-based models for classifying geographic atrophy (GA) subtypes using Optical Coherence Tomography (OCT) scans across four clinical classification tasks. DesignRetrospective comparative study evaluating three DL architectures on OCT data with two experimental approaches. Subjects455 OCT volumes (258 Central GA [CGA], 74 Non-Central GA [NCGA], 123 no GA [NGA]) from 104 patients at Atrium Health Wake Forest Baptist. For GA versus age-related macula...
Predicted journal destinations
1
Ophthalmology Science
15 training papers
2
Translational Vision Science & Technology
18 training papers
3
Scientific Reports
701 training papers
4
npj Digital Medicine
85 training papers
5
PLOS ONE
1737 training papers
6
PLOS Digital Health
88 training papers
7
Nature Communications
483 training papers
8
eLife
262 training papers
9
Computers in Biology and Medicine
39 training papers
10
Journal of Medical Internet Research
81 training papers
11
BMJ Open
553 training papers
12
Cureus
64 training papers
13
F1000Research
28 training papers
14
Frontiers in Neuroscience
29 training papers
15
JAMA Network Open
125 training papers
16
Brain
69 training papers
17
NeuroImage
36 training papers