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支持向量机在CT鉴别诊断肾脏上皮样血管平滑肌脂肪瘤与肾透明细胞癌中的应用 被引量:5

The Application Value of Support Vector Machine in CT Differential Diagnosis of Renal Epithelioid Angiomyolipoma and Clear Cell Renal Cell Carcinoma
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摘要 目的探讨支持向量机在CT鉴别诊断肾脏上皮样血管平滑肌脂肪瘤(epithelioid angiomyolipoma,EAML)的CT与肾透明细胞癌(clear cell renal cell carcinoma,cc RCC)中的应用价值。方法搜集70例经病理证实的肾脏肿瘤(EAML、cc RCC病变各35例),采用支持向量机法综合分析其CT特征表现,判定其所属类型。结果支持向量机法(support vector machine,SVM)对EAML病变的诊断正确率为100%;对cc RCC病变的诊断正确率为94.59%;总体平均判别正确率为97.14%;训练集诊断正确率为97.30%;测试集诊断正确率为96.97%;与bagging和adaboost分类算法诊断符合率相接近。结论支持向量机法有助于CT鉴别诊断EAML和cc RCC,可用于辅助日常阅片工作,尤其是年轻医师或基层医院医师的工作。 Objective To evaluate the application value of support vector machines in the differential diagnosis of renal epithelioid angiomyolipoma (EAML) and clear cell renal cell carcinoma (ccRCC). Methods In this study, 70 cases of renal tumors confirmed by pathology (35 cases of EAML and ccRCC) were collected, and the characteristics of CT features were analyzed by support vector machine method, Results The diagnostic accuracy of support vector machine (SVM) for EAML lesions was 100%.The diagnostic accuracy of ccRCC lesions was 94.59%. The overall average judgnient accuracy was 97.14%. The diagnostic accuracy of the training set was 97.30%. The diagnostic accuracy of the test set was 96.97%. The coincidence rate is similar to bagging and adaboost classification algorithm. Conclusion Support vector machine method is helpful for CT differential diagnosis of EAML and ccRCC, which can be used to assist in daily work, especially for young doctors or primary hospital physicians.
作者 李晓强 常泰
出处 《中国CT和MRI杂志》 2017年第10期91-94,共4页 Chinese Journal of CT and MRI
关键词 上皮样血管平滑肌脂肪瘤 肾透明细胞癌 CT 支持向量机SVM 诊断 Epithelioid Angiomyolipoma Clear Cell Renal Cell Carcinoma CT SVML Differential Diagnosis
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