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PREDICTING THE RISK OF HEART DISEASES FROM RETINAL IMAGES USING MACHINE LEARNING

  • Unique Paper ID: 166882
  • Volume: 11
  • Issue: 2
  • PageNo: 2222-2227
  • Abstract:
  • Heart diseases are one of the major health issues. The death caused by heart diseases, while individual cases can sometimes be sudden or unexpected, the overall pattern of mortality due to heart diseases tends to follow certain trends and risk factors. Blood vessels are the key factor in detect heart related issues as they are spread throughout our body. Cardiovascular diseases such as hypertension and heart attacks have a significant impact on the structure and function of retinal blood vessels. These changes can be assessed using specialized tools like retinal fundoscopy, which provide images indicating the extent of damage caused by hypertension and heart attacks. Machine learning algorithms can detect preclinical signs that may not be obvious to the naked eye. The goal of our project is to investigate how hypertension and heart attacks affect retinal blood vessels by analysing datasets that include patients both with and without these heart-related conditions. The objective of this research is to innovate novel detection or monitoring methodologies that offer reduced invasiveness, heightened accuracy, cost-effectiveness, and widespread accessibility.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 2
  • PageNo: 2222-2227

PREDICTING THE RISK OF HEART DISEASES FROM RETINAL IMAGES USING MACHINE LEARNING

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