论文标题
使用mRNA表达的神经胶质瘤患者的生存预测和风险估计
Survival prediction and risk estimation of Glioma patients using mRNA expressions
论文作者
论文摘要
神经胶质瘤是预后不良的中枢神经系统肿瘤的致命类型。最近，随着微阵列技术的进步，获得了成千上万的基因表达与神经胶质瘤患者的数据相关数据，从而在许多方面进行了显着分析。因此，基因组学被出现到预后分析领域。在这项工作中，我们确定了与生存有关的7个基因签名，并探索了两种生存预测和风险估计的方法。为了生存预测，我们提出了一种基于概率编程的新型方法，该方法的表现优于现有的传统机器学习算法。通过提出的算法获得平均4倍精度为74％。此外，我们为胶质瘤患者的风险估计构建了预后风险模型。该模型反映了神经胶质瘤患者的存活，对低生存患者的风险很高。
Gliomas are lethal type of central nervous system tumors with a poor prognosis. Recently, with the advancements in the micro-array technologies thousands of gene expression related data of glioma patients are acquired, leading for salient analysis in many aspects. Thus, genomics are been emerged into the field of prognosis analysis. In this work, we identify survival related 7 gene signature and explore two approaches for survival prediction and risk estimation. For survival prediction, we propose a novel probabilistic programming based approach, which outperforms the existing traditional machine learning algorithms. An average 4 fold accuracy of 74% is obtained with the proposed algorithm. Further, we construct a prognostic risk model for risk estimation of glioma patients. This model reflects the survival of glioma patients, with high risk for low survival patients.
