A team of researchers led by Yibai Xiong and Yan Ma of the China Academy of Chinese Medical Sciences trained three different machine-learning models to identify severe COVID-19 cases at admission based on 23 variables, including chest CT results, one clinical feature, and 21 laboratory values. In testing, the best-performing algorithm yielded an area under the curve (AUC) of 0.970.

This type of prediction model could potentially assist clinicians in promptly identifying patients with severe cases of COVID-19, enabling timely treatment and optimization of healthcare resources, according to…