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In Cell ; h5-index 250.0

Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19.

Zhang Kang, Liu Xiaohong, Shen Jun, Li Zhihuan, Sang Ye, Wu Xingwang, Zha Yunfei, Liang Wenhua, Wang Chengdi, Wang Ke, Ye Linsen, Gao Ming, Zhou Zhongguo, Li Liang, Wang Jin, Yang Zehong, Cai Huimin, Xu Jie, Yang Lei, Cai Wenjia, Xu Wenqin, Wu Shaoxu, Zhang Wei, Jiang Shanping, Zheng Lianghong, Zhang Xuan, Wang Li, Lu Liu, Li Jiaming, Yin Haiping, Wang Winston, Li Oulan, Zhang Charlotte, Liang Liang, Wu Tao, Deng Ruiyun, Wei Kang, Zhou Yong, Chen Ting, Lau Johnson Yiu-Nam, Fok Manson, He Jianxing, Lin Tianxin, Li Weimin, Wang Guangyu


AI, COVID-19, SARS-CoV-2, automated diagnosis, computed tomography, deep learning, pneumonia, prognosis analysis