AI-assisted CT imaging analysis for COVID-19 screening: Building and deploying a medical AI system in four weeks

Jin, Shuo; Wang, Bo; Xu, Haibo; Luo, Chuan; Wei, Lai; Zhao, Wei; Hou, Xuexue; Ma, Wenshuo; Xu, Zhengqing; Zheng, Zhuozhao; Sun, Wenbo; Lan, Lan; Zhang, Wei; Mu, Xiangdong; Shi, Chenxi; Wang, Zhongxiao; Lee, Jihae; Jin, Zijian; Lin, Minggui; Jin, Hongbo; Zhang, Liang; Guo, Jun; Zhao, Benqi; Ren, Zhizhong; Wang, Shuhao; You, Zheng; Dong, Jiahong; Wang, Xinghuan; Wang, Jianming; Xu, Wei

The sudden outbreak of novel coronavirus 2019 (COVID-19) increased the diagnostic burden of radiologists. In the time of an epidemic crisis, we hoped artificial intelligence (AI) to help reduce physician workload in regions with the outbreak, and improve the diagnosis accuracy for physicians before they could acquire enough experience with the new disease. Here, we present our experience in building and deploying an AI system that automatically analyzes CT images to detect COVID-19 pneumonia features. Different from conventional medical AI, we were dealing with an epidemic crisis. Working in an interdisciplinary team of over 30 people with medical and / or AI background, geographically distributed in Beijing and Wuhan, we were able to overcome a series of challenges in this particular situation and deploy the system in four weeks. Using 1,136 training cases (723 positives for COVID-19) from five hospitals, we were able to achieve a sensitivity of 0.974 and specificity of 0.922 on the test dataset, which included a variety of pulmonary diseases. Besides, the system automatically highlighted all lesion regions for faster examination. As of today, we have deployed the system in 16 hospitals, and it is performing over 1,300 screenings per day.