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Fig. 6 | Breast Cancer Research

Fig. 6

From: Development of a machine learning-based radiomics signature for estimating breast cancer TME phenotypes and predicting anti-PD-1/PD-L1 immunotherapy response

Fig. 6

Performance of radiomics signature in the training and validation sets. A Diagnostic efficacy of radiomics signature in the training set and three independent validation sets. B Evaluation metrics of radiomics signature in the training set and three independent validation sets. C Comparison of rad-scores for different immunophenotypes, immunotherapy responses, and PD-L1 expression, respectively. * ****, p < 0.0001. **, p < 0.01; ACC, accuracy, SEN, sensitivity, SEP, specificity, PPV, positive predictive value, NPV, negative predictive value

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Breast Cancer Research

ISSN: 1465-542X

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