机器学习预测乳腺癌新辅助治疗后炎症代谢状态改变的模型评价

吴其蓁, 刘启明, 柴烨子, 陶政宇, 王依楠, 郭欣宁, 姜萌, 卜军

Evaluation of machine learning prediction of altered inflammatory metabolic state after neoadjuvant therapy for breast cancer

WU Qizhen, LIU Qiming, CHAI Yezi, TAO Zhengyu, WANG Yinan, GUO Xinning, JIANG Meng, PU Jun

图4 乳腺癌新辅助治疗前后患者的5种模型的多特征分析ROC曲线 Note： A?C. ROC curves of training group (A. WBC+HB+HDL multi-feature ROC curve; B. IL-2R+IL-8 multi-feature ROC curve; C. All features multi-feature ROC curve). D?F. ROC curves of testing group (D. WBC+HB+HDL multi-feature ROC curve; E. IL-2R+IL-8 multi-feature ROC curve; F. All features multi-feature ROC curve).

Fig 4 ROC curves of multi-feature analysis for five models for patients with breast cancer before and after neoadjuvant therapy