COVID-19 severity stratification using quantitative computed tomography analysis

Aim: This study aimed to examine the utility of computer-assisted quantitative assessment chest
 computed tomography (CT) images in stratification Coronavirus Disease 2019 (COVID-19)
 severity.
 Materials and Methods: was designed as a retrospective, single-center and
 included total 142 RT-PCR-confirmed COVID-19 patients. CT findings were visually evaluated
 noted for their morphology distribution characteristics. Visual semi-quantitative score (VSS)
 computer-aided (CQS) calculated. The approach was
 assessed based on its ability predict patients who would require intensive care.
 Results: presence underlying fibrosis, air bubble sign, co-occurrence central peripheral lung area involvement that significantly more commonly
 encountered with care requirements during follow-up period. We found a
 significant positive correlation between VSS CQS (p