U-survival for prognostic prediction of disease progression and mortality of patients with COVID-19

U-survival for prognostic prediction of disease progression and mortality of patients with COVID-19

Janne J. Näppi, Tomoki Uemura, Chinatsu Watari, Toru Hironaka, Tohru Kamiya, Hiroyuki Yoshida

Abstract The rapid increase of patients with coronavirus disease 2019 (COVID-19) has introduced major challenges to healthcare services worldwide. Therefore, fast and accurate clinical assessment of COVID-19 progression and mortality is vital for the management of COVID-19 patients. We developed an automated image-based survival prediction model, called U-survival, which combines deep learning of chest CT images with the established survival analysis methodology of an elastic-net Cox survival model. In an evaluation of 383 COVID-19 positive patients from two hospitals, the prognostic bootstrap prediction performance of U-survival was significantly higher (P 

2021

10.1038/s41598-021-88591-z

Epidemiology and Health

Korean Society of Epidemiology

Science, Medicine