A review on the use of artificial intelligence for medical imaging of the lungs of patients with coronavirus disease 2019
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Chest Imaging - Review
P: 443-448
September 2020

A review on the use of artificial intelligence for medical imaging of the lungs of patients with coronavirus disease 2019

Diagn Interv Radiol 2020;26(5):443-448
1. Department of Innovative Biomedical Visualization, Nagoya University Graduate School of Medicine, Showa-ku, Nagoya, Japan
2. Department of Radiology, Nagoya University Graduate School of Medicine, Showa-ku, Nagoya, Japan
No information available.
No information available
Received Date: 27.04.2020
Accepted Date: 03.05.2020
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ABSTRACT

The results of research on the use of artificial intelligence (AI) for medical imaging of the lungs of patients with coronavirus disease 2019 (COVID-19) has been published in various forms. In this study, we reviewed the AI for diagnostic imaging of COVID-19 pneumonia. PubMed, arXiv, medRxiv, and Google scholar were used to search for AI studies. There were 15 studies of COVID-19 that used AI for medical imaging. Of these, 11 studies used AI for computed tomography (CT) and 4 used AI for chest radiography. Eight studies presented independent test data, 5 used disclosed data, and 4 disclosed the AI source codes. The number of datasets ranged from 106 to 5941, with sensitivities ranging from 0.67–1.00 and specificities ranging from 0.81–1.00 for prediction of COVID-19 pneumonia. Four studies with independent test datasets showed a breakdown of the data ratio and reported prediction of COVID-19 pneumonia with sensitivity, specificity, and area under the curve (AUC). These 4 studies showed very high sensitivity, specificity, and AUC, in the range of 0.9–0.98, 0.91–0.96, and 0.96–0.99, respectively.