Development and evaluation of an artificial intelligence system for COVID-19 diagnosis.
Nat Commun
; 11(1): 5088, 2020 10 09.
Article
em En
| MEDLINE
| ID: mdl-33037212
ABSTRACT
Early detection of COVID-19 based on chest CT enables timely treatment of patients and helps control the spread of the disease. We proposed an artificial intelligence (AI) system for rapid COVID-19 detection and performed extensive statistical analysis of CTs of COVID-19 based on the AI system. We developed and evaluated our system on a large dataset with more than 10 thousand CT volumes from COVID-19, influenza-A/B, non-viral community acquired pneumonia (CAP) and non-pneumonia subjects. In such a difficult multi-class diagnosis task, our deep convolutional neural network-based system is able to achieve an area under the receiver operating characteristic curve (AUC) of 97.81% for multi-way classification on test cohort of 3,199 scans, AUC of 92.99% and 93.25% on two publicly available datasets, CC-CCII and MosMedData respectively. In a reader study involving five radiologists, the AI system outperforms all of radiologists in more challenging tasks at a speed of two orders of magnitude above them. Diagnosis performance of chest x-ray (CXR) is compared to that of CT. Detailed interpretation of deep network is also performed to relate system outputs with CT presentations. The code is available at https//github.com/ChenWWWeixiang/diagnosis_covid19 .
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Pneumonia Viral
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Inteligência Artificial
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Infecções por Coronavirus
Tipo de estudo:
Clinical_trials
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Diagnostic_studies
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Evaluation_studies
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Prognostic_studies
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Screening_studies
Limite:
Adult
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Aged
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Aged80
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article