Abstract
The COVID-19 pandemic has challenged institutions' diagnostic processes worldwide. The aim of this study was to assess the feasibility of an artificial intelligence (AI)-based software tool that automatically evaluates chest computed tomography for findings of suspected COVID-19.Two groups were retrospectively evaluated for COVID-19-associated ground glass opacities of the lungs (group A: real-time polymerase chain reaction positive COVID patients, n=108; group B: asymptomatic pre-operative group, n=88). The performance of an AI-based software assessment tool for detection of COVID-associated abnormalities was compared with human evaluation based on COVID-19 reporting and data system (CO-RADS) scores performed by 3 readers.All evaluated variables of the AI-based assessment showed significant differences between the 2 groups (P
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Gashi, A., Kubik-Huch, R. A., Chatzaraki, V., Potempa, A., Rauch, F., Grbic, S., … Lawal, I. (2021). Detection and characterization of COVID-19 findings in chest CT: Feasibility and applicability of an AI-based software tool. Medicine (United States), 100(41), E27478. https://doi.org/10.1097/MD.0000000000027478
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