首页> 美国卫生研究院文献>Journal of Cellular and Molecular Medicine >Predicting overall survival of patients with hepatocellular carcinoma using a three‐category method based on DNA methylation and machine learning
【2h】

Predicting overall survival of patients with hepatocellular carcinoma using a three‐category method based on DNA methylation and machine learning

机译:基于DNA甲基化和机器学习的三类方法预测肝细胞癌患者的总体生存率

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Hepatocellular carcinoma (HCC) is closely associated with abnormal DNA methylation. In this study, we analyzed 450K methylation chip data from 377 HCC samples and 50 adjacent normal samples in the TCGA database. We screened 47,099 differentially methylated sites using Cox regression as well as SVM‐RFE and FW‐SVM algorithms, and constructed a model using three risk categories to predict the overall survival based on 134 methylation sites. The model showed a 10‐fold cross‐validation score of 0.95 and satisfactory predictive power, and correctly classified 26 of 33 samples in testing set obtained by stratified sampling from high, intermediate and low risk groups.
机译:肝细胞癌(HCC)与异常的DNA甲基化密切相关。在这项研究中,我们分析了TCGA数据库中377个HCC样品和50个相邻正常样品的450K甲基化芯片数据。我们使用Cox回归以及SVM-RFE和FW-SVM算法筛选了47,099个甲基化差异位点,并基于134个甲基化位点,使用三种风险类别构建了预测总生存期的模型。该模型显示10倍的交叉验证得分为0.95,具有令人满意的预测能力,并且通过对来自高,中,低风险组的分层抽样获得的测试集中的33个样本中的26个进行了正确分类。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号