A Deep Learning Approach for COVID-19 8 Viral Pneumonia Screening with X-ray Images

Classification of Chest Radiology Images in Order to Identify Patients with COVID-19 Using Deep Learning Techniques

Background and Aim: Due to the important role of radiological images for identifying patients with COVID-19, creating a model based on deep learning methods was the main objective of this study. Materials and Methods: 15,153 available chest images of normal, COVID-19, and pneumonia individuals which were in the Kaggle data repository was used as dataset of this research. Data preprocessing inc...

Using deep learning on X-ray images to detect threats

VII.19 Airport Baggage Screening with X-Ray Tomography

Badley, R. A., R. A. L. Drake, I. A. Shanks, A. M. Smith, and P. R. Stephenson. 1987. Optical biosensors for immunoassays: the fluorescence capillary-fill device. Philosophical Transactions of the Royal Society of London B 316:143–60. Jumarhon, B., and S. McKee. 1995. On the heat equation with nonlinear and nonlocal boundary conditions. Journal of Mathematical Analysis and Applications 190:806–...

ORF8 ∆382 Mutation: A Possible Viral Prognostic Biomarker for the Severity of the COVID-19

Since the initial onset of the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic from Wuhan, China in December 2019, the virus is now spread all around the world, and the disease is named COVID-19. Based on the WHO report on April 18, 2021, there are now more than 140 million confirmed cases and three millions deaths due to this disease[1]. The virus pathogenesis, cl...

Deep learning for automated skeletal bone age assessment in X-ray images

Skeletal bone age assessment is a common clinical practice to investigate endocrinology, genetic and growth disorders in children. It is generally performed by radiological examination of the left hand by using either the Greulich and Pyle (G&P) method or the Tanner-Whitehouse (TW) one. However, both clinical procedures show several limitations, from the examination effort of radiologists to (m...