Kidney Cancer Detection using Deep Learning Models

Abstract

This study presents two types of Kidney cancer detection one is with the help of images and another one is with the help of blood test samples value. Kidney disease is condition caused either by renal disease of the kidneys. In the present study, Kidney cancer is one of the critical diseases for patient's diagnosis and classification. Early detection and good treatment can avoid or decrease the growth of cancer disease into the final stage where dialysis or renal transplantation is the only way of saving the life of the patient. And another way is with machine learning models with this model the disease at an early stage can be detected, is one of the important tasks in today's world. This research proposed kidney images detection through deep learning models like Convolutional Neural Networks (CNNs), and blood samples dataset values through Artificial Neural Network (ANN) models that can be helpful for the early diagnosis of cancer. The existing studies have mainly used only simple CNN models and have done another classification of kidney images. This research consists of CNN with more convolution layers for classifying images of cancer kidneys and normal kidneys and ANN is used for kidney cancer prediction using dataset values. This research will be helpful for early and accurate diagnosis of kidney cancer to save the lives of many patients. Lastly, there is an application page that contains a code in the backend that predicts whether a person is suffering from a kidney cancer or not.