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

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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7196900/
https://www.ncbi.nlm.nih.gov/pubmed/32416069
http://dx.doi.org/10.1016/j.cell.2020.04.045
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author 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
author_facet 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
author_sort Zhang, Kang
collection PubMed
description 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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spelling pubmed-71969002020-05-04 Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography 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 Cell Resource 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. Elsevier Inc. 2020-06-11 2020-05-04 /pmc/articles/PMC7196900/ /pubmed/32416069 http://dx.doi.org/10.1016/j.cell.2020.04.045 Text en © 2020 Elsevier Inc. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Resource
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
Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography
title Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography
title_full Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography
title_fullStr Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography
title_full_unstemmed Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography
title_short Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography
title_sort clinically applicable ai system for accurate diagnosis, quantitative measurements, and prognosis of covid-19 pneumonia using computed tomography
topic Resource
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7196900/
https://www.ncbi.nlm.nih.gov/pubmed/32416069
http://dx.doi.org/10.1016/j.cell.2020.04.045
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