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用临床和基因组数据动态预测存活率

Dynamic prediction of survival with clinical and genomic data
课程网址: http://videolectures.net/as2011_van_houwelingen_prediction/  
主讲教师: Hans C. van Houwelingen
开课单位: 莱顿大学
开课时间: 信息不详。欢迎您在右侧留言补充。
课程语种: 英语
中文简介:
生物统计学的一个重要临床应用是建立诊断时患者预后的统计模型。在癌症中,通常通过x年生存率来判断预后,例如x=1、5或10。传统的预后以治疗开始时的临床信息为基础,如年龄、性别、肿瘤大小、肿瘤分期等。近十年来,微阵列基因表达、蛋白组质谱数据等新的基因组信息类型逐渐出现。这种新型数据的问题在于它的丰富性。例如,微阵列可以测量成千上万个基因的表达。讲座将讨论三个问题:#如何获得有效的基于高维基因组数据的预测模型。如何评估基因组信息的附加价值。#如何获得健壮的动态预测(后续将提供预测)
课程简介: An important clinical application of biostatistics is the development of statistical models for the prognosis of a patient at the moment of diagnosis. In cancer the usual way of giving a prognosis is by means of the x-year survival probability, with x=1, 5 or 10, for example. Traditionally, the prognosis is based on clinical information at the start of the treatment, like age, gender, size of the tumor, tumor stage etc. In the last decade new types of genomic information have become available like micro-array gene expression and proteomic mass spectrometry data. The problem with this new type of data is its abundance. Micro-arrays can measure the expression of tens of thousands of genes, for example. The talk will address three issues: # How to obtain valid prognostic model based on high-dimensional genomic data. # How to assess the added value of the genomic information. # How to obtain robust dynamic predictions (predictions available later on in the follow-up)
关 键 词: 生物统计学; 重要临床应用; 统计模型
课程来源: 视频讲座网
最后编审: 2019-10-22:cwx
阅读次数: 45