清华大学Guangyu Wang、四川大学Weimin Li、中山大学Tianxin Lin、澳门科技大学Kang Zhang等研究人员合作开发出可用于COVID-19肺炎CT扫描结果进行诊断的AI系统。2020年4月29日，这一研究成果在线发表在《细胞》上。
Author: Kang Zhang, Xiaohong Liu, Jun Shen, Zhihuan Li, Ye Sang, Xingwang Wu, Yunfei Cha, Wenhua Liang, Chengdi Wang, Ke Wang, Linsen Ye, Ming Gao, Zhongguo Zhou, Liang Li, Jin Wang, Zhizhong Yang, Huimin Cai, Jie Xu, Lei Yang, Wenjia Cai, Wenqin Xu, Shaoxu Wu, Wei Zhang, Shanping Jiang, Lianghong Zheng, Xuan Zhang, Li Wang, Liu Lu, Jiaming Li, Haiying Wu, Winston Wang, Oulan Li, Charlotte Zhang, Liang Liang, Tao Wu, Ruiyun Deng, Kang Wei, Yong Zhou, Ting Chen, Johnson Yiu-Nam Lau, Manson Fok, Jianxing He, Tianxin Lin, Weimin Li, Guangyu Wang
Issue&Volume: 2020-04-29
Abstract: Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novelcoronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However,rapid diagnosis and identification of high-risk patients for early intervention arechallenging. Using a large computed Tomography (CT) database from 4,154 patients,we developed an AI system that can diagnose NCP and differentiate it from other commonpneumonia and normal controls. The AI system can assist radiologists and physiciansin performing a quick diagnosis especially when the health system is overloaded. Significantly,our AI system identified important clinical markers that correlated with the NCP lesionproperties. Together with the clinical data, our AI system was able to provide accurateclinical prognosis that can aid clinicians to consider appropriate early clinicalmanagement and allocate resources appropriately. We have made this AI system availableglobally to assist the clinicians to combat COVID-19.
DOI: 10.1016/j.cell.2020.04.045
Source: https://www.cell.com/cell/fulltext/S0092-8674(20)30551-1