Özet:

Early detection plays an important role in controlling the spread path of the SARS-CoV-2 virus caused by COVID-19. The reverse transcription-polymerase chain reaction (RT-PCR) is often used in the diagnosis of coronavirus. However, the tests cannot give the correct result in every stage of the disease, and the time it takes to get the results facilitates the process of the disease’s spread. In early stages, medical radiological imaging methods, such as computer tomography (BT), are used to diagnose COVID-19, which are less connected to contact and can give faster results. The use of deep learning approaches in the detection of disease through radiological images has been very interesting in recent years. In this study, a deep learning-based approach was used for the purpose of rapid and accurate diagnosis of COVID-19 from lung radiological images. The success assessment of the approach was carried out on an open source COVID-19 data set.

Anahtar Kelimeler:

Özet:

COVID-19 is a disease caused by the SARS-CoV-2 virus. Early detection and diagnosis of COVID-19 play an important role in controlling the spread of the disease. Reverse transcription-polymerase chain reaction (RT-PCR) is frequently used in the diagnosis of coronavirus. However, tests cannot give accurate results at every stage of the disease. The time taken for test results facilitates the spread of the disease. Medical radiological imaging methods such as X-ray (X-Ray) and Computed Tomography (CT) are used to diagnose COVID-19 in the early stages, which are less contact-dependent and can provide faster results. The use of deep learning approaches in disease detection through radiological images very popular in recent years. In this study, a deep learning-based approach was used for rapid and accurate diagnosis of COVID-19 from lung radiological images. The performance of the approach was examined on an open-source COVID-19 dataset.