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Fig. 2 | Breast Cancer Research

Fig. 2

From: Multimodal recurrence risk prediction model for HR+/HER2- early breast cancer following adjuvant chemo-endocrine therapy: integrating pathology image and clinicalpathological features

Fig. 2

Evaluation of deep learning model performance and Kaplan-Meier analysis of WSI-based risk score. (A). Performance metrics (AUC, accuracy, precision, recall, and F1 score) of the four deep learning models: CTP-ACMIL, RoiCTP-ACMIL, CTP-CLAM and RoiCTP-CLAM. (B-C). ROC curves for recurrence risk score of the RoiCTP-ACMIL model in 5-fold cross-validation. (D). Heatmap distribution of WSI-based risk score and patient recurrence status for the RoiCTP-ACMIL model. (E-F). Kaplan-Meier curves for RFS in the validation set and test set. HR and 95% CI were calculated using the Cox proportional hazards model. P values were calculated using the log-rank test. WSI, whole slide image; RFS, recurrence-free survival

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Breast Cancer Research

ISSN: 1465-542X

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