基于MRI影像组学的BI-RADS 3-5类乳腺病变三分类
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韩冰,徐晶,王远军,王中领
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Classification of BI-RADS 3-5 Breast Lesions Based on MRI Radiomics
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HAN Bing,XU Jing,WANG Yuanjun,WANG Zhongling
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表5 基于各种特征的不同模型对乳腺病变BI-RADS 3-5类的诊断效能
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Table 5 Diagnostic efficacy of different models based on various features for classification of BI-RADS 3-5 breast lesions
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特征 | 模型 | 准确率 | Kappa系数 | 海明损失 | Micro AUC | Macro AUC | 平扫特征 | SVM | 64.86% | 0.419 | 0.297 | 0.848 | 0.820 | | RF | 70.27% | 0.421 | 0.333 | 0.878 | 0.846 | | KNN | 70.27% | 0.421 | 0.333 | 0.830 | 0.769 | | LR | 71.43% | 0.421 | 0.333 | 0.858 | 0.882 | 增强特征 | SVM | 70.27% | 0.428 | 0.297 | 0.895 | 0.847 | | RF | 86.49% | 0.428 | 0.297 | 0.928 | 0.862 | | KNN | 76.19% | 0.445 | 0.297 | 0.875 | 0.828 | | LR | 78.57% | 0.428 | 0.297 | 0.948 | 0.929 | 融合特征 | SVM | 81.25% | 0.606 | 0.224 | 0.881 | 0.855 | | RF | 87.50% | 0.676 | 0.188 | 0.951 | 0.988 | | KNN | 78.38% | 0.606 | 0.224 | 0.886 | 0.867 | | LR | 81.25% | 0.606 | 0.224 | 0.961 | 0.989 |
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