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Fig. 4 | BMC Medical Informatics and Decision Making

Fig. 4

From: Multi-label annotation of text reports from computed tomography of the chest, abdomen, and pelvis using deep learning

Fig. 4

Overview of the RBAs. (Top) The findings section of each report was extracted, then the text was converted to lowercase and each sentence was tokenized. The RBA was deployed on each sentence, and the number of diseases was counted using the multi-organ descriptor first and then the single-organ descriptor logic. If no disease labels were detected, the normal descriptor logic was applied. This process was repeated for each disease allowing a report to be positive for one or more diseases or normal for each organ system. (Bottom) The normal, multi-organ, and single organ descriptor logics

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