Barın, SezinKaya, FurkanÖzgül, EsraGüraksın, Gür Emre2023-04-102023-04-1020212148-2446http://doi.org/10.29130/dubited.866124https://search.trdizin.gov.tr/yayin/detay/496688https://hdl.handle.net/20.500.12684/11719The coronavirus, which appeared in Wuhan city of China and named COVID-19 , spread rapidly and caused the death of many people. Early diagnosis is very important to prevent or slow the spread. The first preferred method by clinicians is real-time reverse transcription-polymerase chain reaction (RT-PCR). However, expected accuracy values cannot be obtained in the diagnosis of patients in the incubation period. Therefore, common lung devastation in COVID-19 patients were considered and radiological lung images were used to diagnose. In this study, automatic COVID-19 diagnosis was made from posteroanterior (PA) chest X-Ray images by deep learning method. In the study, using two different deep learning methods, classification was made with different dataset combinations consisting of healthy, COVID, bacterial pneumonia and viral pneumonia X-ray images. The results show that the proposed deep learning-based system can be used in the clinical setting as a supplement to RT-PCR test for early diagnosisen10.29130/dubited.866124info:eu-repo/semantics/openAccessDeep LearningX-ray ImagingCOVID- 19AlexNetGoogleNet AlexNetGoogleNetX-ray GörüntülemeDerin ÖğrenmeCOVİD- 19Article93823496688