Kid-ML: ML For Kidney Malignant Tissues Identification

Abstract

A considerable worldwide medical and health burden is imposed bykidney disease due to its high rates of morbidity and death as well as its higheconomic cost. Imaging tests can be used by doctors to detect kidney tumors orother diseases. Imaging studies include Magnetic Resonance Imaging(MRI),Computed Tomography(CT) scan, and ultrasound scan which consume a lot oftime from doctors to detect kidney cancers through them. In order to help doctorsto identify tumors in their early stages, they can use simple MachineLearning(ML) techniques or Deep Learning techniques through diagnostics andpredictions applications. A rise in interest in deep learning algorithms, which areArtificially Intelligently (AI) based, on a worldwide scale has enabled recentimprovements in medical imaging and kidney segmentation. Deep Learningtechniques which are AI-based can offer and identify the kidney tumor in a moreefficient method, allowing for the development of a more effective kidney tumordetection system. An input layer, one or more hidden layers, and an output layer