Skip to content
Log in
Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Explainable deep learning models for kidney stone classification using axial CT scans

Muhammad Zeeshan Burki Rashid Naseem Abdul Wajahat Muhammad Rizwan Nazeer Muhammad
Aug 2026 · Network Modeling Analysis in Health Informatics and Bioinformatics · Vol 15 · 0 citations · 40 references

TL;DR

Enhanced Grad-CAM visualizations suggest that lightweight architectures like EfficientNet-B0 and MobileNetV2 achieve statistically comparable performance to heavier models while being computationally efficient, which implies that they can be utilized in the clinical environment with limited resources.

DOI Semantic Scholar
View source

Similar papers

Open access Aug 2026

Deep Learning-Based Detection of Renal Abnormalities from CT Images: A Study on a Bangladeshi Cohort

An AI-driven computed tomography diagnostic system for the automated detection and classification of renal abnormalities in the Bangladeshi population is presented and Xception showed the best overall performance, indicating its strong capability for reliable renal abnormality classification from CT images.

Mithila Yeasmin Mitu · 0 citations
Open access Sep 2026

AI-Assisted Multiclass Kidney CT Pathology Classification for Urological Imaging: An Optimized Hybrid Deep Learning Framework

Kidney CT imaging plays a central role in the urological diagnosis of renal cysts, calculi, solid tumors, and normal renal parenchyma. Although deep learning has shown promise for automated CT-based kidney pathology classification, existing approaches frequently rely on single-architecture models and lack systematic hy...

M. Ağdaş, F. Karahüseyinoğlu · 0 citations
Open access 2026

A Deep Learning Approach for Automated Kidney Tumor Classification

A hybrid architecture in which ResNet50 is employed for localized spatial feature extraction, while Vision Transformer enables global contextual learning to automatically classify kidney tumors into multiple classes is proposed.

Hivi Kamal, W. M. Abduallah · 0 citations
Conference Jul 2026

Optimizing InceptionV3 through Network Pruning for Lung Disease Detection in Chest X-Ray Images

Lung disease remains a major global health concern, and accurate diagnosis using chest X-ray images plays a crucial role in supporting effective clinical decision-making. The contribution of this work lies in empirically demonstrating how internal redundancy removal through standard magnitude-based pruning can improve...

Joshua Pinem, Widi Astuti, A. Adiwijaya · 0 citations
Conference Jul 2026

A Comprehensive Review on Kidney Stone Detection using Machine Learning and Deep Learning Techniques

Kidney stone disease is a common urological disease, which impacts a significant proportion of the population across the globe. It should be diagnosed early and properly because in the cases that are not properly dealt with, the complications may include obstruction of urine and permanent damage to the kidneys. Compute...

Vangapandu Venkata Kalyani, V. M. Moorthy · 0 citations
Feb 2026

Current Medical Imaging

Pelvic MRI fistulogram offers better contrast in soft-tissue and multi-planar image viewing, which are very important for accurate diagnosis and efficient treatment planning, and has become the ultimate choice for the evaluation of RVF.

Faikah Awang, Muhammad Khalis, A. Karim et al. · 25 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.