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Deep learning for chest radiograph diagnosis: A retrospective . . . Deep learning with DCNNs can accurately classify TB at chest radiography with an AUC of 0 99 and an independent board-certified cardiothoracic radiologist blindly interpreted the images to evaluate a potential radiologist-augmented workflow
Sci-Hub | Deep learning for chest radiograph diagnosis: A retrospective . . . Rajpurkar, P , Irvin, J , Ball, R L , Zhu, K , Yang, B , Mehta, H , … Lungren, M P (2018) Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists PLOS Medicine, 15 (11), e1002686 doi:10 1371 journal pmed 1002686
Deep learning for chest radiograph diagnosis: A retrospective . . . The results of this study demonstrate that the dataset can be used to train models with high diagnostic accuracy for predicting the likelihood of 14 different diseases in abnormal chest radiographs, enabling accurate and efficient discrimination between different types of chest radiographs
[1901. 07031] CheXpert: A Large Chest Radiograph Dataset with . . . We present CheXpert, a large dataset that contains 224,316 chest radiographs of 65,240 patients We design a labeler to automatically detect the presence of 14 observations in radiology reports, capturing uncertainties inherent in radiograph interpretation