Development and validation of a deep-learning-based diagnostic model for drug-induced liver injury using computed tomography images

Figure 1 Pipeline of deep-learning-based pyrrolizidine-alkaloid induced hepatic sinusoidal obstruction syndrome classification based on computed tomography images. CT: Computed tomography; DL: Deep learning; AUC: Area under the curve; ROC: Receiver operating characteristic.

Figure 2 Flowchart of included patients. PA-HSOS: Pyrrolizidine-alkaloid-induced hepatic sinusoidal obstruction syndrome; CT: Computed tomography.

Figure 3 Receiver operating characteristic curves and area under the curve of the block-level and patient-level ensembled model results on the internal and external test cohort. A and B: Based on the internal test cohort; C and D: Based on the external test cohort. A and C represent the block-level results, while B and D represent the patient-level results. AUC: Area under the curve; ROC: Receiver operating characteristic.