Diagnostic performance of deep-learning-based screening methods for diabetic retinopathy in primary care—A meta-analysis

摘要

Background Diabetic retinopathy (DR) affects 10–24% of patients with diabetes mellitus type 1 or 2 in the primary care (PC) sector. As early detection is crucial for treatment, deep learning screening methods in PC setting could potentially aid in an accurate and timely diagnosis.