Chronic Kidney Disease Stage Prediction in HIV Infected Patient using Deep Learning

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GRD Journals- Global Research and Development Journal for Engineering | Volume 6 | Issue 5 | April 2021 ISSN- 2455-5703

Chronic Kidney Disease Stage Prediction in HIV Infected Patient using Deep Learning Dr. Sheshang Degadwala Associate Professor Department of Computer Engineering

Dhairya Vyas Managing Director Shree Drashti Infotech LLP, Nizampura, Vadodara, Gujarat, India

Sigma Institute of Engineering, Vadodara, Gujarat

Abstract The CKD is the worldwide phenomenon with high morbidity and death rates. Chronic renal disease (CKD). Since the early stages of the CKD do not have any symptoms, patients frequently struggle to recognize their condition. HIV-patients are most likely to suffer from critically compromised kidney failure. Early diagnosis of CKD allows patients to get prompt medication to improve the disease's development. The suggested CNN deep learning model for the organization of the CKD phases observed with HIV is presented in this article. The credits of CKD patients are carried out on site. In the Chronic Kidney Disease phase predicted, CNN is 99% accurate with the PCA model. Keywords- Chronic Kidney Disease, Stage, Machine Learning, Deep Learning, Convolution Nural Network, Principle Componend Analysis

I. INTRODUCTION Chronic kidney disease is an increasing global health concern (CKD). This is an incurable illness linked to a rise in morbidity and death, an increased risk for many other illnesses, including cardiac failure and higher costs for health care. More than two million patients worldwide undergo dialysis or kidney transplants to remain alive, but this figure may only account for 10% of people requiring survival therapy [2]. In only five rich nations, the bulk of the 2 million individuals who receive anti-kidney disease therapy constitute 12 percent of the world's population. In contrast, in about 100 developed countries just 20% of the world's population is handled, representing about half of the world's population. More than a million people die each year from unexplained kidney disease because of the enormous financial cost of dialysis and renal transplant care in 112 low-income countries [5]. When this form of circumstance occurs, filters do not function properly in order to allow HIV to infect the cells of the kidney, HIV may damage glomeruli (nephrons). If any drugs used to treat HIV are not closely controlled, the nephrons can damage the kidney. Since several studies were carried out to identify CKD or not and to detect CKD steps. The relationship between CKD and HIV is, however, novel. The rate of incidence and prevalence of CKD in the context of HIV infection varies in all areas with significant differences and on the same continent. Variety depends on a number of factors such as kidney function tests, CKD definition, genetic variation, prevention program, access to a health care system and the implementation of integrated ART. The first obstacle to overcome is proper kidney function tests because no methods have been used to measure the glomerular filtration rate (eGFR) certified in PLWH.

Fig. 1: Causes of Chronic Kidney Disease [16]

Therefore, it is very important to detect, control, and control the disease early. It is necessary to predict the progression of CKD with due accuracy due to its strong and subtle nature in the early stages, as well as the heterogeneity of the patient. CKD is often described in stages of severity. Clinical decisions are influenced by the stage, whether the patient is progressing, and the level of progression. Also, defining the stage of the disease is very important as it provides many indications that support the determination of the necessary interventions and treatment. All rights reserved by www.grdjournals.com

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