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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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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7939450/
https://www.ncbi.nlm.nih.gov/pubmed/33686526
http://dx.doi.org/10.1007/s10278-021-00424-7
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author 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.
author_facet 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.
author_sort Fernández-Miranda, P. Menéndez
collection PubMed
description 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 < .0001) and those with higher specificity decreased their sensitivity (p < .0001). Users who sent more answers achieved better accuracy (p = .0002). The application COVID-19 TRAINING provides a revolutionary tool to learn the necessary skills to evaluate COVID-19 on CXR. Diagnosis training applications could provide a new original manner of evaluation for medical professionals based on their diagnostic accuracy values, and an efficient method to collect valuable data for research purposes.
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spelling pubmed-79394502021-03-09 Developing a Training Web Application for Improving the COVID-19 Diagnostic Accuracy on Chest X-ray 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. J Digit Imaging Article 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 < .0001) and those with higher specificity decreased their sensitivity (p < .0001). Users who sent more answers achieved better accuracy (p = .0002). The application COVID-19 TRAINING provides a revolutionary tool to learn the necessary skills to evaluate COVID-19 on CXR. Diagnosis training applications could provide a new original manner of evaluation for medical professionals based on their diagnostic accuracy values, and an efficient method to collect valuable data for research purposes. Springer International Publishing 2021-03-08 2021-04 /pmc/articles/PMC7939450/ /pubmed/33686526 http://dx.doi.org/10.1007/s10278-021-00424-7 Text en © Society for Imaging Informatics in Medicine 2021
spellingShingle Article
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.
Developing a Training Web Application for Improving the COVID-19 Diagnostic Accuracy on Chest X-ray
title Developing a Training Web Application for Improving the COVID-19 Diagnostic Accuracy on Chest X-ray
title_full Developing a Training Web Application for Improving the COVID-19 Diagnostic Accuracy on Chest X-ray
title_fullStr Developing a Training Web Application for Improving the COVID-19 Diagnostic Accuracy on Chest X-ray
title_full_unstemmed Developing a Training Web Application for Improving the COVID-19 Diagnostic Accuracy on Chest X-ray
title_short Developing a Training Web Application for Improving the COVID-19 Diagnostic Accuracy on Chest X-ray
title_sort developing a training web application for improving the covid-19 diagnostic accuracy on chest x-ray
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7939450/
https://www.ncbi.nlm.nih.gov/pubmed/33686526
http://dx.doi.org/10.1007/s10278-021-00424-7
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