• Cardiovascular disease is one of the most fatal conditions in the present world.
  • In under a minute, an artificial intelligence program can take a picture of the back of a person’s eye and by analyzing the strength of the blood vessels that feed the retina find clues that may point to higher risks of a stroke or heart attack.
  • A unifying goal of work like this is to develop new disease detection or monitoring approaches that are less invasive, more accurate, cheaper and more readily available.
  • However, one restriction to potential broad population-level applicability of efforts to extract biomarkers from fundus photos is getting the fundus photos themselves, which requires specialized imaging equipment and a trained technician.


  • Very few systems use the available clinical data for Classification purposes and even if they do ,they are restricted by the large number of association rules  that apply.
  • Diagnosis of the condition solely depends upon the Doctors’s intuition and patient’s records.


  • Detection is not possible at an earlier stage.
  • In the existing system, practical use of various collected data is time consuming .


  • We have developed an artificial intelligence (AI) system that can analyze eye scans taken during a routine visit to an optician or eye clinic and identify patients at a high risk of a heart attack.
  • Changes to the tiny blood vessels in the retina are indicators of broader vascular disease, including problems with the heart.
  • The training data is trained by using proposed machine learning algorithm RNN classification clustering and Adaboost. algorithm is explained in detail.
  • High performance and accuracy rate.
  • RNN Classification is very flexible and is widely in various domains with high rates of success.


    Software Requirements:

    • Front End – Anaconda IDE
    • Backend – SQL
    • Language – Python 3.8

    Hardware Requirements

    • •Hard Disk: Greater than 500 GB
    • •RAM: Greater than 4 GB
    • •Processor: I3 and Above

    Including Packages


    • * Base Paper
    • * Complete Source Code
    • * Complete Documentation
    • * Complete Presentation Slides
    • * Flow Diagram
    • * Database File
    • * Screenshots
    • * Execution Procedure
    • * Readme File
    • * Addons
    • * Video Tutorials
    • * Supporting Softwares

    Specialization =======================

    • * 24/7 Support * Ticketing System
    • * Voice Conference
    • * Video On Demand 
    • * Remote Connectivity
    • * Code Customization
    • * Document Customization 
    • * Live Chat Support

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