This study presents a novel approach to kidney stone diagnosis using convolutional neural
networks (CNN), applied to computed tomography (CT) images. The research addresses the …

The rising risk of diabetes, particularly in emerging countries, highlights the importance of
early detection. Manual prediction can be a challenging task, leading to the need for …

The human body comprises various essential organs, including the lungs, which are
responsible for the exchange of gases during respiration. However, the modern lifestyle and …

Deep learning enables effective predictions. But deep structures face some challenges on
human interpretability compared to conventional techniques, eg, fuzzy inference systems. It …

Kidney failure, also called as end-stage renal disease is the final stage of chronic kidney
disease (CKD). Kidney failure cannot be revered and is the life-threatening if left untreated …

Chronic kidney disorder is a global health problem involving the repercussions of impaired
kidney function and kidney failure. A kidney stone is a kidney scenario that impairs kidney …

In diagnosing kidney stone disease, clinical specialists often apply medical imaging
techniques such as CT, X‐Ray and US. Among these imaging techniques, X‐Ray is …

Kidney disease is a major health problem that affects millions of people around the world.
Human kidney problems can be diagnosed with the help of computed tomography (CT) …

In this study, a novel methodology is proposed to combine deep learning techniques and
metaheuristic optimization to enable early diagnosis of patients with kidney stone using CT …

Deep learning techniques for ordinal classification have recently gained significant attention.
Predicting an ordinal variable, that is, a variable that demonstrates a natural relationship …