Before revision:  We also found that the inclusion of radiomic-embedded maps improved DL model predictions of clinical outcomes. Conclusions: We demonstrate the potential for computerized analysis of baseline CXR in predicting disease outcomes in COVID-19 patients .
After revision:  Combined classifiers using both radiomics and expert severity scores resulted in mAUCs of 0.79+/-0.04 and 0.83+/-0.04 for each prediction task, demonstrating improvement over either artificial intelligence or radiologist interpretation alone .