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Diabetic Retinopathy (DR) is a severe problem associated with diabetes, which can cause permanent vision loss if not identified and managed promptly. Early detection of DR is essential for effective intervention and treatment. Traditionally, diagnosing DR has depended on manual evaluations by ophthalmologists, a process that can be labor-intensive, subjective, and prone to inconsistencies. This study states the potential of machine learning (ML) and deep learning (DL) techniques using SVM and ResNet50 models to automate the detection and classification of diabetic retinopathy using retinal images.

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Diabetic Retinopathy Prediction: Leveraging Machine Learning and Deep Learning for Early Detection

  • 会议论文

  • 发表日期：

    2025年

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  • Kulvinder Singh,
  • Shivam Chopra,
  • Manas Sanghi,
  • Om

摘要

Diabetic Retinopathy (DR) is a severe problem associated with diabetes, which can cause permanent vision loss if not identified and managed promptly. Early detection of DR is essential for effective intervention and treatment. Traditionally, diagnosing DR has depended on manual evaluations by ophthalmologists, a process that can be labor-intensive, subjective, and prone to inconsistencies. This study states the potential of machine learning (ML) and deep learning (DL) techniques using SVM and ResNet50 models to automate the detection and classification of diabetic retinopathy using retinal images.