Fig. 2.

Validation accuracy for nine models. Classification accuracy, based on top prediction, of the UCSF chest radiograph validation set is graphed for the nine different models, grouped by pre-training and fine-tuning methods. Error bars mark 95 % confidence intervals. Labels above the graph and to the right of the legend show pooled comparisons and chi-square test results. For the models fine-tuned on original radiographs, validation sets consisted of 376 original radiographs. For models fine-tuned on augmented radiographs, validation sets consisted of 39,856 augmented radiographs