Diagnosis of Diabetic Retinopathy Using Machine Learning Techniques
Sabahath Saimeen
, Akshaya N. A , Astra Natasha , Shrishti Kumari , Suryakanth B
Diabetic Retinopathy, Machine Learning, SVM, MATLAB, Retinal Fundus Images.
The World Health Organization has prophesied that by 2030, there will be around 366 million individuals with diabetes around the world. Various inconveniences happen because of diabetes. Some of them are cardiovascular infection, neuropathy, nephropathy, retinopathy, skin harms, hearing afflictions and others. Universally, diabetic retinopathy has now turned into the fifth commonest reason for visual impairment around the world. Early location of diabetic retinopathy (DR) is essential to forestall vision misfortune and visual impairment. Manual discovery of diabetic retinopathy is a dreary errand. PC - supported framework improves on the work. This can likewise be utilized as a screening device in clinical camps.
"Diagnosis of Diabetic Retinopathy Using Machine Learning Techniques ", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 7, page no.632 - 636, July-2022, Available :https://ijsdr.org/papers/IJSDR2206101.pdf
Volume 7
Issue 7,
July-2022
Pages : 632 - 636
Paper Reg. ID: IJSDR_200789
Published Paper Id: IJSDR2206101
Downloads: 000347062
Research Area: Engineering
Country: Bengaluru, Karnataka, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
