Diagnostic Accuracy of a Device for the Automated Detection of Diabetic Retinopathy in a Primary Care Setting

Cited by (116)

Items 101–116 of 116

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3. Updating Diagnoses for Speed and Accuracy: Using AI, Cameras, Assays, and More
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4. Is automated screening for diabetic retinopathy indeed not yet ready as stated by Grauslund et al.?
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5. Screening of Diabetic Retinopathy and its stages using Deep Neural Networks on Retinal optical Images
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6. Deep learning-based system for the research of pluripotent stem cell-derived cells
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7. Pigeon M etheuristic Optimized Generative Adversarial Networks and ARKFCM Algorithms for retinal V essel Segmentation and Classification
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8. Diabetic Retinopathy Detection Using Artificial Intelligence: A Review
   Gulshan, Vikas Chauhan · 2024 · International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)
9. Pre-trained Vision Transformer With Masked Autoencoder for Automated Diabetic Macular Edema Detection from Optical Coherence Tomography Images
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10. Additional file 1 of Single retinal image for diabetic retinopathy screening: performance of a handheld device with embedded artificial intelligence
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11. AI-Based Measurement Tools for Intrinsic Capacity in Older Adults: Scoping Review
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12. Advances and challenges from pathological mechanisms to intelligent quantified diagnosis in diabetic optic neuropathy
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13. Effectiveness of screening modalities for early detection of diabetic retinopathy: a systematic review and meta-analysis of tele-ophthalmology, AI-based tools, and conventional methods
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14. Autonomous AI for Diabetic Retinopathy Screening: Evidence, Regulation, and Health-System Fit
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15. An Explainable Deep Learning Framework for Early Detection of Diabetic Retinopathy
    Ramya. A. B, Radhika. K, Nirmaladevi K · 2026 · International Conference on Data Science for Cyber-Physical Systems Resilience using Advanced Applications (ICDCA)
16. ACCESS2 study: the potential for autonomous AI to mitigate disparities in diabetic retinopathy screening in youth
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