Quantification of Fluid Resolution and Visual Acuity Gain in Patients With Diabetic Macular Edema Using Deep Learning: A Post Hoc Analysis of a Randomized Clinical Trial.

Journal: JAMA ophthalmology

PMID: 32722799

Abstract

IMPORTANCE: Large amounts of optical coherence tomographic (OCT) data of diabetic macular edema (DME) are acquired, but many morphologic features have yet to be identified and quantified.

Authors

Philipp K Roberts

Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Wolf-Dieter Vogl
Bianca S Gerendas

Christian Doppler Laboratory for Ophthalmic Image Analysis (OPTIMA), Department of Ophthalmology, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.
Adam R Glassman

Jaeb Center for Health Research, Tampa, Florida.
Hrvoje Bogunović

Christian Doppler Laboratory for Ophthalmic Image Analysis (OPTIMA), Department of Ophthalmology, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.
Lee M Jampol

Department of Ophthalmology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois.
Ursula M Schmidt-Erfurth

Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.

Keywords

Aged Algorithms Angiogenesis Inhibitors Deep Learning Diabetic Retinopathy Female Follow-Up Studies Humans Intravitreal Injections Macular Edema Male Middle Aged Ranibizumab Receptors, Vascular Endothelial Growth Factor Recombinant Fusion Proteins Retrospective Studies Subretinal Fluid Vascular Endothelial Growth Factor A Visual Acuity

External Resources

View on PubMed Access via DOI PubMed (32722799)

Quantification of Fluid Resolution and Visual Acuity Gain in Patients With Diabetic Macular Edema Using Deep Learning: A Post Hoc Analysis of a Randomized Clinical Trial.

Abstract

Authors

Keywords

External Resources

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