@article{article_1654887, title={Use of Chest X-ray Images and Artificial Intelligence Methods for Early Diagnosis of COVID-19}, journal={Politeknik Dergisi}, pages={1–1}, year={2025}, DOI={10.2339/politeknik.1654887}, author={A. Mustafa, Maral and Erdem, O. Ayhan and Söğüt, Esra}, keywords={Covid-19 classification, VGG16, resnet, inception, CNN}, abstract={The worldwide epidemic brought on by COVID-19 has substantially hurt people’s health. To discover and treat ill people, given the significant usage of efficient screening and diagnostic methods, as well as a crucial way to this deadly illness. One strategy that might be used to help with COVID-19 early diagnosis is to make use of X-ray pictures of individuals’ chests. Different Computer Aided Diagnosis (CAD) methods have been created to aid doctors in doing this work by providing them more extra information and suggestions. This investigation uses pictures of chest X-rays taken to create a CAD method for COVID-19 illness. Convolutional Neural Network (CNN), Resnet50, Xception, Densnet, Mobilenet, VGG16, Resnet152v2, and Inceptionv3 will use in the investigation to examine the pictures and remark on automatic detection and categorization of COVID-19 cases. The effectiveness of each method will be examined on a big collection of chest X-ray pictures to identify its accuracy and reliability in detecting COVID-19 cases. The result of this investigation could be used to design an effective and reliable tool for COVID-19 diagnosis and evaluation.}, publisher={Gazi University}