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Results Thirty-seven features were used to establish a radiomics signature, which demonstrated better predictive performance than did the image features model constructed using tumor size and intratumoral vessels in the training and validation cohorts (p 0.05). Decision curve analysis verified that the radiomics nomogram had the best clinical utility compared with the other models. Conclusion The radiomics nomogram developed in the present study is a promising tool to predict tumor necrosis and facilitate preoperative clinical decision-m
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