MOLECULAR SCIENCES AND APPLICATIONS
Print ISSN: 2944-9138, E-ISSN: 2732-9992 An Open Access International Journal of Molecular Sciences and Applications
Volume 4, 2024
Image-based Chronic Kidney Disease Diagnosis Using 2D Convolutional Neural Networks in the Context of a Comprehensive Artificial Intelligence-Driven Healthcare System
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Abstract: Reports published by the World Health Organization (WHO) indicate that noncommunicable diseases (NCDs) including chronic kidney disease (CKD) are among the top ten causes of mortality worldwide. Accurate and early diagnosis of chronic kidney disease could save lives, ameliorate deleterious effects and dramatically improve quality of life. This paper presents a system that harnesses convolutional neural networks (CNNs) that could be incorporated into a comprehensive artificial intelligence (AI)-driven healthcare system for the automated diagnosis of chronic kidney disease. Utilizing publicly available image datasets featuring images representing normal kidney states, cysts, tumors and kidney stones split into training and validation samples, the system achieves an accuracy approximating 97% on the training and validation datasets.
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Keywords: Chronic Kidney Disease (CKD), Artificial Intelligence (AI), Deep Learning (DL), Convolutional Neural Network (CNN), Two-dimensional (2D) Convolutional Neural Network (2D CNN), Healthcare System, CT Image
Pages: 135-143
DOI: 10.37394/232023.2024.4.13