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@article{179781,
        author = {Prarthana Y T and Nisarga R Kumar and Rachana H V and Nandan C V and Madhu C K},
        title = {Identification of Memory Loss disease by Ocular  Biomarkers using Deep Learning Models},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {9148-9154},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179781},
        abstract = {This study investigates the use of deep learning techniques to analyze retinal images captured through Optical Coherence Tomography Angiography (OCTA) for the detection of Alzheimer’s disease (AD). By assessing changes in retinal blood vessel properties, such as flow and density, the method identifies patterns linked to AD. The research expands on existing approaches and integrates clinical insights to create a non- invasive, cost-effective tool for early diagnosis. It also emphasizes the importance of specific regions of the retina in the detection process, offering valuable information for medical professionals and advancing the understanding of retinal biomarkers as- sociated with AD. The results highlight the potential of this approach to improve the accuracy and accessibility of diagnosing neurodegenerative diseases.},
        keywords = {OCTA, Alzheimer’s Disease, Polar Transformation},
        month = {June},
        }