تطوير نموذج باستخدام الشبكات العصبية لتشخيص حصاوى الكلى

Abstract

The kidneys are an important vital organ for preserving the human life, so it its safety must be assured. this research helps to develop a model using neural network algorithms, specifically convolutional neural network in artificial intelligence to help diagnose kidney stones to invest time and effort in diagnosis and improve efficiency and accuracy, regarding the rate of spread of kidney stone disease in Sudan, the multiplicity of its types and the difficulty of seeing it many cases which leads to errors in diagnosis and complications in the future, such as kidney failure resulting from stones that are not discovered in early stages. This research aims to help doctors in discovering kidney stones and predicting kidney failure.in this research, a model based on artificial intelligence algorithm to detect stones in kidney images, a set of medical images of 104 images of kidney stone patients was used the performance of the model was measured and we recorded 100% of the convolutional neural networks applied to the image data set for patients with kidney stones. The proposed model obtained better accuracy than previous studies. The research concluded with asset of recommendations that help doctors in early detection of kidney stones according to the analysis of the data and the importance of the features and features selected based on the convolutional neural networks model .using the proposed model ,doctors can predict kidney failure before it occurs and prevent it by analyzing the data of kidney patients examination records and classifying medical images of kidney patients, which helps in early detection of kidney stones and diseases.