Exploring the capabilities of a lightweight CNN model in accurately identifying renal abnormalities: Cysts, stones, and tumors, using LIME and SHAP

M Bhandari, P Yogarajah, MS Kavitha, J Condell - Applied Sciences, 2023 - mdpi.com
Kidney abnormality is one of the major concerns in modern society, and it affects millions of
people around the world. To diagnose different abnormalities in human kidneys, a narrow …

A multi-class deep learning model for early lung cancer and chronic kidney disease detection using computed tomography images

A Bhattacharjee, S Rabea, A Bhattacharjee… - Frontiers in …, 2023 - frontiersin.org
Lung cancer is a fatal disease caused by an abnormal proliferation of cells in the lungs.
Similarly, chronic kidney disorders affect people worldwide and can lead to renal failure and …

Application of visual transformer in renal image analysis

Y Yin, Z Tang, H Weng - BioMedical Engineering OnLine, 2024 - Springer
Abstract Deep Self-Attention Network (Transformer) is an encoder–decoder architectural
model that excels in establishing long-distance dependencies and is first applied in natural …

Evaluating Retinal Disease Diagnosis with an Interpretable Lightweight CNN Model Resistant to Adversarial Attacks

M Bhandari, TB Shahi, A Neupane - Journal of Imaging, 2023 - mdpi.com
Optical Coherence Tomography (OCT) is an imperative symptomatic tool empowering the
diagnosis of retinal diseases and anomalies. The manual decision towards those anomalies …

Kidney Tumor Classification on CT images using Self-supervised Learning

E Özbay, FA Özbay, FS Gharehchopogh - Computers in Biology and …, 2024 - Elsevier
One of the most common diseases affecting society around the world is kidney tumor. The
risk of kidney disease increases due to reasons such as consumption of ready-made food …

Adaptive Local Binary Pattern: A Novel Feature Descriptor for Enhanced Analysis of Kidney Abnormalities in CT Scan Images using ensemble based Machine …

T Hossain, F Sayed, S Islam - arXiv preprint arXiv:2404.14560, 2024 - arxiv.org
The shortage of nephrologists and the growing public health concern over renal failure have
spurred the demand for AI systems capable of autonomously detecting kidney abnormalities …

Spatial Attention-guided Deep Learning for Accurate Kidney Disease Classification in CT Scans

MN Islam, M Al Mamun, MF Faruk… - … on Computer and …, 2023 - ieeexplore.ieee.org
Kidney diseases are globally prevalent and often lead individuals to seek urgent medical
attention due to severe discomfort. The timely identification of these conditions necessitates …

RenalNet: An End-to-End Hybrid Deep Learning and Ensemble Model for Accurate Kidney Disorder Classification

F Haque, MAI Siddique… - 2024 3rd International …, 2024 - ieeexplore.ieee.org
Kidney disorders are a major public health issue affecting millions worldwide. Renal calculi
and cancer are prevalent, causing chronic kidney disease (CKD). Artificial intelligence can …

Transfer Learning Empowered Multi-Class Classification of Kidney Diseases: A Deep Learning Approach

G Sharma, V Anand, R Chauhan… - … on Advancement in …, 2024 - ieeexplore.ieee.org
The growing rate of chronic kidney disease and a shortage of renal specialists make renal
dysfunction a major worldwide health concern. This study, which makes use of technological …

Detection of Kidney Disease in X-Ray Images Using Machine Learning on MobileNetV3 CNN Model

KS Gill, V Anand, R Chauhan, P Singh… - 2023 2nd International …, 2023 - ieeexplore.ieee.org
Classifying kidney pictures or patient data according to various disease categories, such as
stages of chronic kidney disease (CKD), PKD, kidney stones, renal tumours, and other …