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

Overview

Journal Cell

Publisher Cell Press

Specialty Cell Biology

Date 2020 May 17

PMID 32416069

Citations 315

Authors

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

Wenqin Xu

Shaoxu Wu

Wei Zhang

Shanping Jiang

Lianghong Zheng

Xuan Zhang

Li Wang

Liu Lu

Jiaming Li

Haiping Yin

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

Affiliations

Soon will be listed here.

Abstract

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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