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Development and prospective validation of COVID-19 chest X-ray screening model for patients attending emergency departments.


ABSTRACT: Chest X-rays (CXRs) are the first-line investigation in patients presenting to emergency departments (EDs) with dyspnoea and are a valuable adjunct to clinical management of COVID-19 associated lung disease. Artificial intelligence (AI) has the potential to facilitate rapid triage of CXRs for further patient testing and/or isolation. In this work we develop an AI algorithm, CovIx, to differentiate normal, abnormal, non-COVID-19 pneumonia, and COVID-19 CXRs using a multicentre cohort of 293,143 CXRs. The algorithm is prospectively validated in 3289 CXRs acquired from patients presenting to ED with symptoms of COVID-19 across four sites in NHS Greater Glasgow and Clyde. CovIx achieves area under receiver operating characteristic curve for COVID-19 of 0.86, with sensitivity and F1-score up to 0.83 and 0.71 respectively, and performs on-par with four board-certified radiologists. AI-based algorithms can identify CXRs with COVID-19 associated pneumonia, as well as distinguish non-COVID pneumonias in symptomatic patients presenting to ED. Pre-trained models and inference scripts are freely available at https://github.com/beringresearch/bravecx-covid .

SUBMITTER: Drozdov I 

PROVIDER: S-EPMC8516957 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Development and prospective validation of COVID-19 chest X-ray screening model for patients attending emergency departments.

Drozdov Ignat I   Szubert Benjamin B   Reda Elaina E   Makary Peter P   Forbes Daniel D   Chang Sau Lee SL   Ezhil Abinaya A   Puttagunta Srikanth S   Hall Mark M   Carlin Chris C   Lowe David J DJ  

Scientific reports 20211014 1


Chest X-rays (CXRs) are the first-line investigation in patients presenting to emergency departments (EDs) with dyspnoea and are a valuable adjunct to clinical management of COVID-19 associated lung disease. Artificial intelligence (AI) has the potential to facilitate rapid triage of CXRs for further patient testing and/or isolation. In this work we develop an AI algorithm, CovIx, to differentiate normal, abnormal, non-COVID-19 pneumonia, and COVID-19 CXRs using a multicentre cohort of 293,143 C  ...[more]

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