Efficient Prediction of Kidney Disorders using Deep Learning

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Authors: Mohammad Naseeruddin, M Pachhaiammal Alias Priya, Choriyev Muzaffar, Jumaniyozov Kuvondik Yo'ldashevich, Sadullayeva Moxinur, D. Stalin
Cited by: 6
References: 11

Abstract

The world is moving with innovative technologies in health care to track human health parameters finding health diseases. Artificial intelligence plays an important role in prediction of health diseases. Now a days kidney diseases effect's on human health and deaths are happening throughout the world due to kidney disorders. Kidney disorders such Chronic Kidney Disease (CKD), Polycystic Kidney Disease (PKD)Kidney Stones, infections, kidney cyst, Glomerulonephritis and kidney stone. It is impossible to recognize the symptoms of the disease in its early stages. Few people are able to anticipate the symptoms of this illness and are aware of it. The illness is regarded as a possible risk factor. Therefore, this paper uses a powerful deep learning framework to prevent these diseases by lowering the risk of contracting them. Deep learning is introduced in proposed research along with machine learning to predict kidney diseases. Convolution Neural Network (CNN) from the deep learning and Support Vector Machine (SVM) from the machine learning used in proposed research to predict kidney disorders. CNN predicts kidney disorders with highest accuracy of 97% over existing methods and SVM.

Fields of Study & Subjects

Artificial Intelligence in Healthcare Kidney Stones and Urolithiasis Treatments Renal and Vascular Pathologies

Publication details

Journal / source
2026 International Conference on AI-Driven Smart Systems and Ubiquitous Computing (ICAUC)
Publisher
IEEE
Pages
893–897
Publication date
19 January 2026