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Coronavirus Disease 2019 (COVID-19) has become an unprecedented public health crisis since December of 2019. Compared with real-time reverse transcription polymerase chain reaction (rRT-PCR), the computer-aided diagnosis machine learning algorithm based on medical images can vastly ease the burden on clinicians. Even so, despite existing hundreds of millions of confirmed cases worldwide, there has not been a mature, large scale, high quality, single standard shared image data set yet, which can lead to some problems. For instance, 1) Because the sources of medical images and the collection standards are not guaranteed, features extracted by the neural network may not be very ideal. 2) Due to the small number of samples, some outliers (e.g., blurry medical images, inconspicuous symptoms) may significantly descend the performance of the model. To address these problems, we propose an …