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EJNMMI Research
Fig. 3 | EJNMMI Research

Fig. 3

From: 18F-FDG PET/CT-based deep learning radiomics predicts 5-years disease-free survival after failure to achieve pathologic complete response to neoadjuvant chemotherapy in breast cancer

Fig. 3

Training and testing cohort of ROC curve and DCA curve. The receiver operating characteristic (ROC) curves of the radiomics model, DL model, clinical models (T, RCB) and combined model in the training cohort (a, b) and validation cohort (c, d). The combined model demonstrated significantly higher AUCs in the training and validation cohorts than other models. Decision curve analysis (DCA) of the radiomics model, DL model and combined model in the training cohort (e, f) and validation cohort (g, h). The x-axis is the threshold probability, and the y-axis measures the net benefit. The combined model received a higher net benefit than the other two models across most ranges of reasonable threshold probabilities

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