Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography | Zendy

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

Open Access

Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography

Author(s) -

Kang Zhang,

Xiaohong Liu,

Jun Shen,

Zhihuan Li,

Ye Sang,

Xingwang Wu,

Yunfei Zha,

Wenhua Liang,

Chengdi Wang,

Ke Wang,

Linsen Ye,

Ming Gao,

Zhongguo Zhou,

Liang Li,

Jin Wang,

Zehong Yang,

Huimin Cai,

Jie Xu,

Lei Yang,

Wenjia Cai,

W. Xu,

Shaoxu Wu,

Wei Zhang,

Shanping Jiang,

Lianghong Zheng,

Xuan Zhang,

Li Wang,

Lu Liu,

Jiaming Li,

Haiping Yin,

Winston Wang,

Oulan Li,

Charlotte Zhang,

Liang Liang,

Tao Wu,

Ruiyun Deng,

Wei Kang,

Yong Zhou,

Ting Chen,

Johnson Yiu-Nam Lau,

Manson Fok,

Jianxing He,

Tianxin Lin,

Weimin Li,

Guangyu Wang

Publication year - 2020

Publication title -

cell

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 26.304

H-Index - 776

eISSN - 1097-4172

pISSN - 0092-8674

DOI - 10.1016/j.cell.2020.04.045

Subject(s) - pneumonia , covid-19 , computed tomography , intensive care medicine , viral pneumonia , coronavirus , radiology , biology , medicine , pathology , disease , infectious disease (medical specialty)

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.

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