期刊论文

Liao, Wei-Hua;Bai, Harrison X.

英文

European Radiology

0938-7994

2022

32

1

205-212

10.1007/s00330-021-08049-8

This study was supported by the Brown COVID-19 Research Seed Award, AWS Diagnostic Development Initiative, RSNA Research Scholar Grant (RSCH2004), and National Institutes of Health/National Cancer Institute R03 grant (R03CA249554) to Dr. Harrison X. Bai, as well as NIH grants (CA223358, DK117297, MH120811, and EB022573) to Dr. Yong Fan. Research reported in this publication was supported by a training grant from the National Institute of Biomedical Imaging and Bioengineering (NIBIB) of the National Institutes of Health under award number 5T32EB1680 and by the National Cancer Institute (NCI) of the National Institutes of Health under Award Number F30CA239407 to K. Chang. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Dr. Xue Feng currently works in Carina Medical, a for-profit organization that develops clinical products.

本校为其他机构

Objectives: Early recognition of coronavirus disease 2019 (COVID-19) severity can guide patient management. However, it is challenging to predict when COVID-19 patients will progress to critical illness. This study aimed to develop an artificial intelligence system to predict future deterioration to critical illness in COVID-19 patients. Methods: An artificial intelligence (AI) system in a time-to-event analysis framework was developed to integrate chest CT and clinical data for risk prediction of future deterioration to critical illness in pat...