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The need for noninvasive diagnostic techniques for early detection and risk assessment is brought to light by the substantial global health burden that cardiovascular diseases (CVDs) continue to impose. To predict the chances of CVD, this research aims to use retinal imaging with the use of different algorithms. The research highlights the capability of AI-driven retinal image analysis by examining the retinal vascular network in order to find microvascular biomarkers linked to CVD and make precise predictions. These findings demonstrate retinal imaging’s efficiency as a potentially valuable method for early detection of CVD.

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Automate Retinal Scanning to Predict the Chances of Cardiovascular Disease

  • 会议论文

  • 发表日期：

    2026年

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  • Kalyani Ghuge,
  • Amit Raut,
  • Nupoor Raut,
  • Pranav Raut,
  • Rashi Bhansali,
  • Chayank Rathod

摘要

The need for noninvasive diagnostic techniques for early detection and risk assessment is brought to light by the substantial global health burden that cardiovascular diseases (CVDs) continue to impose. To predict the chances of CVD, this research aims to use retinal imaging with the use of different algorithms. The research highlights the capability of AI-driven retinal image analysis by examining the retinal vascular network in order to find microvascular biomarkers linked to CVD and make precise predictions. These findings demonstrate retinal imaging’s efficiency as a potentially valuable method for early detection of CVD.