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首页> 外文会议>IEEE International Conference on Industrial Engineering and Engineering Management >Preoperative Analysis for Clinical Features of Unsuspected Gallbladder Cancer Based on Random Forest
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Preoperative Analysis for Clinical Features of Unsuspected Gallbladder Cancer Based on Random Forest

机译：基于随机森林的可疑胆囊癌临床特征的术前分析

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With the incidence of unsuspected gallbladder cancer (UGC) increasing, the difference of preoperative features between unsuspected gallbladder cancer and gallbladder cancer diagnosed before operation arose doctors' attention recently. In this study, firstly, chi square test was adopted to analyze the difference of two groups and select out the difference variables. Then, the random forest was proposed to establish the classification model whose accuracy evaluated by area under curve was 0.7310. Meanwhile, the model identified the critical classification factors using variable importance, which adopted the method of mean decrease in accuracy. Finally, the results of two methods showed that clinical features of biliary calculi, cholecystolithiasis history, gallbladder polyps and family history of malignancy, serum CEA level, jaundice, cholecystitis history and abdominal pain were important factors in preoperative assessment of unsuspected gallbladder cancer. What's more, the feature of time of cholecystitis history should not be ignored for preoperative assessment of UGC patients.
机译：随着意外的胆囊癌（UGC）发病率的增加，近来意外的胆囊癌与术前诊断出的胆囊癌之间的术前特征差异引起了医生的关注。在这项研究中，首先，采用卡方检验分析两组的差异并选择差异变量。然后，提出了利用随机森林建立分类模型的方法，该模型的准确度以曲线下面积为0.7310。同时，该模型使用变量重要性来识别关键分类因子，并采用均值降低的方法。最后，两种方法的结果表明胆结石的临床特征，胆囊结石病史，胆囊息肉和恶性家族史，血清CEA水平，黄疸，胆囊炎史和腹痛是术前评估未怀疑胆囊癌的重要因素。此外，对于UGC患者的术前评估，不应忽略胆囊炎病史的特点。

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