Abstract

Diabetic retinopathy (DR) is a medical condition that can affect the patient's retina and cause leaks in the blood due to diabetes mellitus. The increase in cases of diabetes limits existing manual testing capability. Today new algorithms are becoming very important for assisted diagnosis. Effective diabetes diagnosis can benefit the victims and reduce the negative harmful effects, including blindness. If not treated in a timely manner, this disorder can cause different symptoms from mild vision problems to total blindness. Early signs of DR are the hemorrhages, hard exudates, and micro-aneurysms (HEM) that occur in the retina. Timely diagnosis of HEM is important for avoiding blindness This paper presents PSO feature selection algorithms with three classifications for the detection of Diabetic retinopathy using python.

Highlights

  • Diabetic retinopathy is the undergoing changes that take place in blood sugar levels throughout the capillary of the retinal system

  • There are two types of diabetic!retinopathy: Early diabetic!retinopathy Commonly known as -non proliferative diabetic retinopathy (NPDR) which occurs when there isn’t growth/proliferating of new capillary

  • Decrease the level your risk of diabetic retinopathy when you suffer from diabetes by doing the following:

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Summary

INTRODUCTION

Diabetic retinopathy is the undergoing changes that take place in blood sugar levels throughout the capillary of the retinal system. Some vessels may swell up in some cases, and fluid leaks into the back of the eye. These could swell and drop in the capillary. They could close, blocking the flow of blood. Anomalous new capillary often grow up on the retina. All these improvements will rob your eyesight. DR was not leading symptoms initially, just low vision complications. The you have far more diabetes, and the less sugar on your blood regulated, the greater the probability that you will experience this eye complication. The eye looks for new capillary development

Types of diabetic retinopathy
Vijayashree, School of Computer Science and Engineering, VIT,Vellore
Symptoms
Risk Factors
Prevention
Statistics
LITERATURE REVIEW
METHODOLOGY
RESULT
Findings
CONCLUSION
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