The Role of Artificial Intelligence in Enhancing Diabetic Retinopathy Lesion Detection: A Review

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dc.contributor.authorLakshmi, KSen_US
dc.contributor.authorSargunam, B.en_US
dc.date.accessioned2025-05-12T09:44:03Z
dc.date.available2025-05-12T09:44:03Z
dc.date.issued2024-12
dc.description.abstractDiabetic retinopathy represents a significant microvascular complication associated with prolonged diabetes mellitus and serves as a leading cause of blindness, particularly in developing nations. For the patient's vision to be adequately preserved, early identification of DR is essential. In order to treat the disease, the patient must maintain his or her current level of vision since the disease is irreversible. The Clinical diagnosis demands significant time and the specialized knowledge of an experienced ophthalmologist and also identifying the disease features in images is also more challenging, particularly in the early stages of the disease when disease features are less noticeable. Therefore, deep learning algorithms have been used for the early diagnosis of DR in recent years, and medical image analysis utilising machine learning has demonstrated to be effective in evaluating retinal fundus images. This review's objective is to go over the numerous Deep learning techniques for automated computer-aided analysis of microaneurysms, haemorrhages, and exudates were also addressed, along with a knowledge gap in DR identification. As part of future research, this review seeks to systematize the available algorithms for ease of use and guidance by researchers.en_US
dc.identifier.affiliationsResearch Scholar, Department of Electronics and Communication Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, Indiaen_US
dc.identifier.affiliationsProfessor, Department of Electronics and Communication Engineering, School of Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, Indiaen_US
dc.identifier.citationLakshmi KS, Sargunam B.. The Role of Artificial Intelligence in Enhancing Diabetic Retinopathy Lesion Detection: A Review. Journal of Clinical and Biomedical Sciences. 2024 Dec; 14(4): 121-128en_US
dc.identifier.issn2319-2453
dc.identifier.issn2231-4180
dc.identifier.placeIndiaen_US
dc.identifier.urihttps://imsear.searo.who.int/handle/123456789/247447
dc.languageenen_US
dc.publisherSri Devaraj Urs Academy of Higher Educationen_US
dc.relation.issuenumber4en_US
dc.relation.volume14en_US
dc.source.urihttps://doi.org/10.58739/jcbs/v14i4.94en_US
dc.subjectDiabetic Retinopathy Reviewen_US
dc.subjectMicroaneurysmsen_US
dc.subjectHaemorrhagesen_US
dc.subjectExudatesen_US
dc.subjectRed Lesionsen_US
dc.subjectDeep Learningen_US
dc.titleThe Role of Artificial Intelligence in Enhancing Diabetic Retinopathy Lesion Detection: A Reviewen_US
dc.typeJournal Articleen_US
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