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A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19)

European Radiology · 2021 · Vol. 31(8) · pp. 6096–6104

Shuai Wang✉(Tianjin Medical University Cancer Institute and Hospital)Bo-Kyeong Kang(Tianjin University)Jinlu Ma(First Affiliated Hospital of Xi'an Jiaotong University)Xianjun Zeng(Nanchang University)Mingming Xiao(Tianjin Medical University Cancer Institute and Hospital)Jia Guo(National Supercomputing Center of Tianjin)Mengjiao Cai(First Affiliated Hospital of Xi'an Jiaotong University)Jingyi Yang(First Affiliated Hospital of Xi'an Jiaotong University)Yaodong Li(Wuhan No. 7 Hospital)Xiangfei Meng(First Affiliated Hospital of Xi'an Jiaotong University)Bo Xu(Tianjin Medical University Cancer Institute and Hospital)

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Abstract

• The study evaluated the diagnostic performance of a deep learning algorithm using CT images to screen for COVID-19 during the influenza season. • As a screening method, our model achieved a relatively high sensitivity on internal and external CT image datasets. • The model was used to distinguish between COVID-19 and other typical viral pneumonia, both of which have quite similar radiologic characteristics.

COVID-19 diagnosis using AI Radiomics and Machine Learning in Medical Imaging Artificial Intelligence in Healthcare and EducationCoronavirus disease 2019 (COVID-19)MedicineGold standard (test)DiseaseNeuroradiologyPneumoniaOutbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)AlgorithmArtificial intelligence