Cardiac Risk Assessment Through Retinal Images
Cardiovascular disease (CVD) is the leading cause of death across the globe. Therefore, detection at an early stage is all the more crucial. In this project, retinal images captured during a routine eye examination are used for the prediction of heart attack by deep learning and machine learning. Im...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2025-01-01
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| Series: | ITM Web of Conferences |
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| Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2025/05/itmconf_iccp-ci2024_01007.pdf |
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| author | Reddy L. Manojav Deekshitha M. Sree G. Meghana Padmini K. |
| author_facet | Reddy L. Manojav Deekshitha M. Sree G. Meghana Padmini K. |
| author_sort | Reddy L. Manojav |
| collection | DOAJ |
| description | Cardiovascular disease (CVD) is the leading cause of death across the globe. Therefore, detection at an early stage is all the more crucial. In this project, retinal images captured during a routine eye examination are used for the prediction of heart attack by deep learning and machine learning. Improvement in quality of images, highlights on blood vessels, extracting meaningful features like shape of vessel, and density that relates heart health. The approach will be hybrid, based on a combination of a neural classifier RNN using clustering and AdaBoost for generating highly accurate predictive outputs as well as providing an assessment score for potential issues concerning heart conditions. It is a non-invasive cost-effective procedure, fast, easy, and may be conducted along with regular eye checks to encourage early intervention and better health. |
| format | Article |
| id | doaj-art-0e556bc6cae044a5ae6df514e332fb85 |
| institution | DOAJ |
| issn | 2271-2097 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | ITM Web of Conferences |
| spelling | doaj-art-0e556bc6cae044a5ae6df514e332fb852025-08-20T03:02:18ZengEDP SciencesITM Web of Conferences2271-20972025-01-01740100710.1051/itmconf/20257401007itmconf_iccp-ci2024_01007Cardiac Risk Assessment Through Retinal ImagesReddy L. Manojav0Deekshitha M.1Sree G. Meghana2Padmini K.3Department of CSE, Sreenidhi Institute of Science and TechnologyDepartment of CSE, Sreenidhi Institute of Science and TechnologyDepartment of CSE, Sreenidhi Institute of Science and TechnologyDepartment of CSE, Sreenidhi Institute of Science and TechnologyCardiovascular disease (CVD) is the leading cause of death across the globe. Therefore, detection at an early stage is all the more crucial. In this project, retinal images captured during a routine eye examination are used for the prediction of heart attack by deep learning and machine learning. Improvement in quality of images, highlights on blood vessels, extracting meaningful features like shape of vessel, and density that relates heart health. The approach will be hybrid, based on a combination of a neural classifier RNN using clustering and AdaBoost for generating highly accurate predictive outputs as well as providing an assessment score for potential issues concerning heart conditions. It is a non-invasive cost-effective procedure, fast, easy, and may be conducted along with regular eye checks to encourage early intervention and better health.https://www.itm-conferences.org/articles/itmconf/pdf/2025/05/itmconf_iccp-ci2024_01007.pdfcardiovascular disease (cvd)heart attack risk predictiondeep learningnoninvasive screeningeye fundus imagesand blood vessel analysis |
| spellingShingle | Reddy L. Manojav Deekshitha M. Sree G. Meghana Padmini K. Cardiac Risk Assessment Through Retinal Images ITM Web of Conferences cardiovascular disease (cvd) heart attack risk prediction deep learning noninvasive screening eye fundus images and blood vessel analysis |
| title | Cardiac Risk Assessment Through Retinal Images |
| title_full | Cardiac Risk Assessment Through Retinal Images |
| title_fullStr | Cardiac Risk Assessment Through Retinal Images |
| title_full_unstemmed | Cardiac Risk Assessment Through Retinal Images |
| title_short | Cardiac Risk Assessment Through Retinal Images |
| title_sort | cardiac risk assessment through retinal images |
| topic | cardiovascular disease (cvd) heart attack risk prediction deep learning noninvasive screening eye fundus images and blood vessel analysis |
| url | https://www.itm-conferences.org/articles/itmconf/pdf/2025/05/itmconf_iccp-ci2024_01007.pdf |
| work_keys_str_mv | AT reddylmanojav cardiacriskassessmentthroughretinalimages AT deekshitham cardiacriskassessmentthroughretinalimages AT sreegmeghana cardiacriskassessmentthroughretinalimages AT padminik cardiacriskassessmentthroughretinalimages |