1. Deep learning-based single-shot prediction of differential effects of anti-VEGF treatment in patients with diabetic macular edema

    Deep learning-based single-shot prediction of differential effects of anti-VEGF treatment in patients with diabetic macular edema

    Anti-vascular endothelial growth factor (VEGF) agents are widely regarded as the first line of therapy for diabetic macular edema (DME) but are not universally effective. An automatic method that can predict whether a patient is likely to respond to anti-VEGF therapy can avoid unnecessary trial and error treatment strategies and promote the selection of more effective first-line therapies. The objective of this study is to automatically predict the efficacy of anti-VEGF treatment of DME in individual patients based on optical coherence tomography (OCT) images. We performed a retrospective study of 127 subjects treated for DME with three consecutive injections of ...

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