Abstract
The paper examines the features of viral pneumonias that in the future may be caused by highly pathogenic viruses (HPCoVs) (SARS-CoV-2, MERS-CoV, SARS-CoV), H5N1, H5N7 and influenza A (H1N1) pdm. Rapidly progressive viral pneumonia that develops in these diseases can lead to a fatal complication – acute respiratory distress syndrome (ARDS). Confirmation and refutation of the diagnosis of ARDS today is a difficult task that requires the development and improvement of diagnostic methods. To compare the diagnostic effectiveness of the methods, the possibility of using criteria and parametric recognition models was considered. The discrimination model was built on the basis of the quadratic normalized Euclidean distance between the vectors of mean values by state of quantities. The perspective of the work is to improve methods for assessing diagnostic criteria and severity biomarkers using a discrimination model based on quadratic notched Euclidean distance, which will allow improving the detection of ARDS – a fatal complication of respiratory system infection with highly pathogenic viruses.