Developing a Training Web Application for Improving the COVID-19 Diagnostic Accuracy on Chest X-ray

In December 2019, a new coronavirus known as 2019-nCoV emerged in Wuhan, China. The virus has spread globally and the infection was declared pandemic in March 2020. Although most cases of coronavirus disease 2019 (COVID-19) are mild, some of them rapidly develop acute respiratory distress syndrome....

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Bibliographic Details
Published in:Journal of digital imaging 2021-04, Vol.34 (2), p.242-256
Main Authors: Fernández-Miranda, P. Menéndez, Bellón, P. Sanz, del Barrio, A. Pérez, Iglesias, L. Lloret, García, P. Solís, Aguilar-Gómez, F., González, D. Rodríguez, Vega, J. A.
Format: Article
Language:English
Subjects:
Accuracy
Applications programs
Chest
Coronaviruses
COVID-19
Diagnosis
Imaging
Medical diagnosis
Medical imaging
Medical personnel
Medicine
Medicine & Public Health
Pandemics
Radiology
Respiratory distress syndrome
Thorax
Training
Viral diseases
Viruses
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Summary:In December 2019, a new coronavirus known as 2019-nCoV emerged in Wuhan, China. The virus has spread globally and the infection was declared pandemic in March 2020. Although most cases of coronavirus disease 2019 (COVID-19) are mild, some of them rapidly develop acute respiratory distress syndrome. In the clinical management, chest X-rays (CXR) are essential, but the evaluation of COVID-19 CXR could be a challenge. In this context, we developed COVID-19 TRAINING , a free Web application for training on the evaluation of COVID-19 CXR. The application included 196 CXR belonging to three categories: non-pathological , pathological compatible with COVID-19 , and pathological non-compatible with COVID-19 . On the training screen, images were shown to the users and they chose a diagnosis among those three possibilities. At any time, users could finish the training session and be evaluated through the estimation of their diagnostic accuracy values: sensitivity, specificity, predictive values, and global accuracy. Images were hand-labeled by four thoracic radiologists. Average values for sensitivity, specificity, and global accuracy were .72, .64, and .68. Users who achieved better sensitivity registered less specificity ( p  
ISSN:0897-1889
1618-727X
DOI:10.1007/s10278-021-00424-7