Radiographic findings in COVID-19: Comparison between AI and radiologist
Context: As the burden of COVID-19 enhances, the need of a fast and reliable screening method is imperative. Chest radiographs plays a pivotal role in rapidly triaging the patients. Unfortunately, in low-resource settings, there is a scarcity of trained radiologists. Aim: This study evaluates and co...
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doaj-494ef7c497144ed5b1d0991f4879cd782021-07-15T16:29:30ZengThieme Medical and Scientific Publishers Pvt. Ltd.Indian Journal of Radiology and Imaging0971-30261998-38082021-01-0131S87S9310.4103/ijri.IJRI_777_20Radiographic findings in COVID-19: Comparison between AI and radiologistArsh Sukhija0Mangal Mahajan1Priscilla C Joshi2John Dsouza3Nagesh DN Seth4Karamchand H Patil5Departments of Radiodiagnosis and Imaging and Community Medicine, Bharati Vidyapeeth Deemed to be University Medical College and Hospital, Pune, Maharashtra, IndiaDepartments of Radiodiagnosis and Imaging and Community Medicine, Bharati Vidyapeeth Deemed to be University Medical College and Hospital, Pune, Maharashtra, IndiaDepartments of Radiodiagnosis and Imaging and Community Medicine, Bharati Vidyapeeth Deemed to be University Medical College and Hospital, Pune, Maharashtra, IndiaDepartments of Radiodiagnosis and Imaging and Community Medicine, Bharati Vidyapeeth Deemed to be University Medical College and Hospital, Pune, Maharashtra, IndiaDepartments of Radiodiagnosis and Imaging and Community Medicine, Bharati Vidyapeeth Deemed to be University Medical College and Hospital, Pune, Maharashtra, IndiaDepartments of Community Medicine, Bharati Vidyapeeth Deemed to be University Medical College and Hospital, Pune, Maharashtra, IndiaContext: As the burden of COVID-19 enhances, the need of a fast and reliable screening method is imperative. Chest radiographs plays a pivotal role in rapidly triaging the patients. Unfortunately, in low-resource settings, there is a scarcity of trained radiologists. Aim: This study evaluates and compares the performance of an artificial intelligence (AI) system with a radiologist in detecting chest radiograph findings due to COVID-19. Subjects and Methods: The test set consisted of 457 CXR images of patients with suspected COVID-19 pneumonia over a period of three months. The radiographs were evaluated by a radiologist with experience of more than 13 years and by the AI system (NeuraCovid, a web application that pairs with the AI model COVID-NET). Performance of AI system and the radiologist were compared by calculating the sensitivity, specificity and generating a receiver operating characteristic curve. RT-PCR test results were used as the gold standard. Results: The radiologist obtained a sensitivity and specificity of 44.1% and 92.5%, respectively, whereas the AI had a sensitivity and specificity of 41.6% and 60%, respectively. The area under curve for correctly classifying CXR images as COVID-19 pneumonia was 0.48 for the AI system and 0.68 for the radiologist. The radiologist’s prediction was found to be superior to that of the AI with a P VALUE of 0.005. Conclusion: The specificity and sensitivity of detecting lung involvement in COVID-19, by the radiologist, was found to be superior to that by the AI system.http://www.thieme-connect.de/DOI/DOI?10.4103/ijri.IJRI_777_20artificial intelligencechest radiographscovid pneumoniarapid triaging |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Arsh Sukhija Mangal Mahajan Priscilla C Joshi John Dsouza Nagesh DN Seth Karamchand H Patil |
spellingShingle |
Arsh Sukhija Mangal Mahajan Priscilla C Joshi John Dsouza Nagesh DN Seth Karamchand H Patil Radiographic findings in COVID-19: Comparison between AI and radiologist Indian Journal of Radiology and Imaging artificial intelligence chest radiographs covid pneumonia rapid triaging |
author_facet |
Arsh Sukhija Mangal Mahajan Priscilla C Joshi John Dsouza Nagesh DN Seth Karamchand H Patil |
author_sort |
Arsh Sukhija |
title |
Radiographic findings in COVID-19: Comparison between AI and radiologist |
title_short |
Radiographic findings in COVID-19: Comparison between AI and radiologist |
title_full |
Radiographic findings in COVID-19: Comparison between AI and radiologist |
title_fullStr |
Radiographic findings in COVID-19: Comparison between AI and radiologist |
title_full_unstemmed |
Radiographic findings in COVID-19: Comparison between AI and radiologist |
title_sort |
radiographic findings in covid-19: comparison between ai and radiologist |
publisher |
Thieme Medical and Scientific Publishers Pvt. Ltd. |
series |
Indian Journal of Radiology and Imaging |
issn |
0971-3026 1998-3808 |
publishDate |
2021-01-01 |
description |
Context: As the burden of COVID-19 enhances, the need of a fast and reliable screening method is imperative. Chest radiographs plays a pivotal role in rapidly triaging the patients. Unfortunately, in low-resource settings, there is a scarcity of trained radiologists. Aim: This study evaluates and compares the performance of an artificial intelligence (AI) system with a radiologist in detecting chest radiograph findings due to COVID-19. Subjects and Methods: The test set consisted of 457 CXR images of patients with suspected COVID-19 pneumonia over a period of three months. The radiographs were evaluated by a radiologist with experience of more than 13 years and by the AI system (NeuraCovid, a web application that pairs with the AI model COVID-NET). Performance of AI system and the radiologist were compared by calculating the sensitivity, specificity and generating a receiver operating characteristic curve. RT-PCR test results were used as the gold standard. Results: The radiologist obtained a sensitivity and specificity of 44.1% and 92.5%, respectively, whereas the AI had a sensitivity and specificity of 41.6% and 60%, respectively. The area under curve for correctly classifying CXR images as COVID-19 pneumonia was 0.48 for the AI system and 0.68 for the radiologist. The radiologist’s prediction was found to be superior to that of the AI with a P VALUE of 0.005. Conclusion: The specificity and sensitivity of detecting lung involvement in COVID-19, by the radiologist, was found to be superior to that by the AI system. |
topic |
artificial intelligence chest radiographs covid pneumonia rapid triaging |
url |
http://www.thieme-connect.de/DOI/DOI?10.4103/ijri.IJRI_777_20 |
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