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Advancements in Virtual Health Screening for Diabetic Retinopathy: A Review of AI-Driven Approaches

  • Unique Paper ID: 178665
  • Volume: 11
  • Issue: 12
  • PageNo: 3874-3878
  • Abstract:
  • This paper reviews advancements in virtual health screening tools with a primary focus on diabetic retinopathy detection using artificial intelligence (AI). Diabetic retinopathy, a leading cause of blindness among working-age adults, requires early and accurate detection to prevent severe complications. The integration of AI, particularly deep learning models such as convolutional neural networks (CNNs), has significantly improved diagnostic accuracy and accessibility. This review explores traditional and AI-driven screening methods, the role of publicly available datasets, and deployment challenges in real-world applications. Additionally, it highlights gaps in current research, including data diversity and multi-modal integration. The findings underscore the potential of AI-powered virtual health tools to revolutionize diabetic retinopathy screening, particularly in resource-limited settings, paving the way for more inclusive healthcare solutions.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 12
  • PageNo: 3874-3878

Advancements in Virtual Health Screening for Diabetic Retinopathy: A Review of AI-Driven Approaches

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