Examination of Diabetes Mellitus for Early Prediction and Automatic Detection of Exudates for Diabetic Retinopathy
Lubna Taranum M P1, Rajashekar J S2
1Lubna Taranum M P, Department of IT, DSCE, Bangalore (Karnataka), India.
2Rajashekar J S, Department of IT, DSCE, Bangalore (Karnataka), India.
Manuscript received on 09 December 2019 | Revised Manuscript received on 17 December 2019 | Manuscript Published on 31 December 2019 | PP: 691-694 | Volume-9 Issue-2S December 2019 | Retrieval Number: B10141292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1014.1292S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: More than 42 Cr new diabetes Patients added worldwide as per the World Health Association Annual Report Statistics [3, 7]. The World Health Organization (WHO) reports that there is measurable hike in the number of individual Diabetes cases in the various regions and sectors of WHO Survey . Because of the high level of stress, irrespective of the Gender and income, the Death Toll increasing every year. In this paper, hypothetical analysis-based Survey done of diabetes mellitus for early prediction and Automatic Detection of Exudates for Diabetic Retinopathy [8, 17]. The Hypothetical analysis results indicate the severances of the issue and significant importance of the need for early prediction and Automatic Detection . With hypothetical analysis across various models we proposed to provide a vision into various machine learning models and its prognostic precision in relations of the recital, accuracy improvement from 2+% to 12+%.
Keywords: Exudates, Diabetic Retinopathy (DR).
Scope of the Article: Regression and Prediction