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- W4313352955 abstract "Diabetic macular edema is a leading cause of treatable vision loss in diabetic retinopathy. The advent of newer imaging technology and anti-vascular endothelial growth factor injections have revolutionized the management of diabetic macular edema over the last two decades. Recently, artificial intelligence techniques for computer vision have been increasingly utilized to screen, diagnose, and treat common ophthalmologic conditions. For diabetic macular edema specifically, deep learning can identify and grade diabetic retinopathy on color fundus photos and SD-OCT imaging. Fully convolutional neural networks can now accurately segment retinal layers and quantify fluid volumes via SD-OCT imaging, providing objective measurements of treatment response and anatomical outcomes. Concurrent analysis of multiple imaging techniques, including fluorescein angiography and OCT angiography, further augments the diagnostic and prognostic accuracy of these algorithms. Future work will be focused on developing personalized management plans for patients with diabetic macular edema." @default.
- W4313352955 created "2023-01-06" @default.
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- W4313352955 date "2022-01-01" @default.
- W4313352955 modified "2023-10-14" @default.
- W4313352955 title "Artificial Intelligence in the Management of Diabetic Macular Edema" @default.
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- W4313352955 doi "https://doi.org/10.1007/978-981-19-7307-9_15" @default.
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