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@article{176720,
        author = {Smita Wagh and Tejas Khatkale and Devshri Khairnar and Yash Mali and Sanika Najan},
        title = {DESIGN AND IMPLEMENTATION OF RETINAL IMAGE BASED HEART DISEASE PREDICTION AND RISK MANAGEMENT USING MACHINE LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {7565-7571},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176720},
        abstract = {Cardiovascular diseases like hypertension and heart attacks impact microvascular structures. Fundus imaging helps detect retinal blood vessel abnormalities linked to these conditions. Machine learning and AI identify preclinical symptoms beyond human observation. This study uses vessel segmentation to analyse retinal vasculature, aiding early heart disease detection, especially in young individuals. Retinal imaging supports diagnosis, treatment planning, and clinical assessment across ophthalmology and cardiology. The findings emphasize vessel segmentation's role in medical diagnostics.},
        keywords = {AI diagnosis, Cardiology, Cardiovascular disease, Fundus imaging, Heart attack, Hypertension, Machine learning, medical image processing, Ophthalmology, Retinal blood vessels, Retinal vessel segmentation.},
        month = {April},
        }