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

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

The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.03. 19.20039354 doi: medRxiv preprint While it was not currently possible to build a general AI that could automatically diagnose every new disease, we could have a generally applicable methodology that allowed us to quickly construct a model targeting a specific one, like COVID-19. The methodology not only included a library of models and training tools, but also the process for data collection, annotation, testing, user interaction design, and clinical deployment. Based on this methodology, we were able to produce the first usable model in 7 days after we received the first batch of data, and conducted additional four iterations in the model in the next 13 days while deploying it in 16 hospitals. The model was performing more than 1,300 screenings per day at the time of writing.