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Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamese
Our best model (CheXpert-pretrained EfficientNet-B2) yields an F1-score of 0. 6989 (95% CI 0. 6740, 0. 7240), AUC of 0. 7912, sensitivity of 0. 7064 and specificity of 0. 8760 for the abnormal diagnosis in general.
Slice-level Detection of Intracranial Hemorrhage on CT Using Deep Descriptors of Adjacent Slices
In particular, deep convolutional neural networks (D-CNNs) have been key players and were adopted by the medical imaging community to assist clinicians and medical experts in disease diagnosis and treatment.
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