Fig. 3: The performance of the PJI supervised and weakly supervised learning models.
From: Clinically applicable optimized periprosthetic joint infection diagnosis via AI based pathology
s- refers to the corresponding test results of the PJI supervised learning model, and w- refers to the corresponding test results of the PJI weakly supervised learning model. The red line represents the ROC curve of the PJI supervised learning model, and the blue line represents the ROC curve of the PJI weakly supervised learning model. a Image-level comparison of sensitivity and specificity. b Patient-level comparison of sensitivity and specificity. c Image-level accuracy, recall, and F1 score of the models. d Patient-level accuracy, recall, and F1 score of the models. e Image-level ROC curves for the two models. f Patient-level ROC curves for the two models. g The degree of data dispersion at the image level. The weakly supervised model has a mean ± standard deviation of 0.03433 ± 0.02211 for the negative set and 0.2059 ± 0.05993 for the positive set; the supervised model has 0.03780 ± 0.02328 and 0.2614 ± 0.1009, respectively. h Loss curves for the PJI supervised learning model. i Loss curves for the PJI weakly supervised learning model.
