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ABSTRACT: Objectives
An artificial intelligence model was adopted to identify mild COVID-19 pneumonia from computed tomography (CT) volumes, and its diagnostic performance was then evaluated.Methods
In this retrospective multicenter study, an atrous convolution-based deep learning model was established for the computer-assisted diagnosis of mild COVID-19 pneumonia. The dataset included 2087 chest CT exams collected from four hospitals between 1 January 2019 and 31 May 2020. The true positive rate, true negative rate, receiver operating characteristic curve, area under the curve (AUC) and convolutional feature map were used to evaluate the model.Results
The proposed deep learning model was trained on 1538 patients and tested on an independent testing cohort of 549 patients. Th
SUBMITTER: Yao JC
PROVIDER: S-EPMC7971359 | biostudies-literature | 2021 Sep
REPOSITORIES: biostudies-literature