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However, because of the restricted amount of labeled information, existing solutions are evaluated on a little collection of test dataset. In this work, we proposed a remedy to this problem by using a multi-task semi-supervised discovering (MTSSL) framework that applied auxiliary jobs which is why sufficient information is publicly available. Specifically, we utilized Pneumonia, Lung Opacity, and Pleural Effusion as additional jobs with the ChesXpert dataset. We illustrated that the primary task of C