Predicting pattern of coronavirus using X-ray and CT scan images

AbstractNovel coronavirus is a disease that can propagate easily with very minute carelessness and with very little physical contact between people. Presently, the world ’s central health institution called the World Health Organization has approved and advised the Reverse Transcription-Polymerase Chain Reaction (RT-PCR) swab test as the most important and effective diagnostic method to confirm if a patient has COVID-19 symptoms or not. This test takes at least a day for revealing the results, depending on the feasible resources in the neighborhood. Moreover, the RT-PCR test gives sometimes false positive results and slow in the process. To keep the potential virus carriers and potential causes of the disease quarantined as early as possible, there is still a requirement for a much faster and more accurate diagnostic process to supplement RT-PCR test of finding the patients affected by the virus. In this regard, radiological images such as X-ray and CT (Computerized Tomography) scan are found to be useful. The X-ray and CT scan have good screening moda lity; they are quick at capturing and finding and widely available around the world. Therefore, a deep learning model, which makes use of CT scan and X-ray images, has been proposed to automate and analyze the diagnostic process by utilizing Convolutional Neural Network (CNN). This model makes use o f InceptionV3 deep learning model, a type of CNN. It is a lightweight deep learning model that is apt for mobile, laptop, and ta...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - Category: Bioinformatics Source Type: research