精确医学与大数据

Precision medicine and big data

为了实现精确医学,需要采集和分析大量数据来量化每个病人.首先讨论了从分子层面到链路层面的数据,同时阐述了使用医疗图像数据的必要性.不同数据类型虽然需要有不同的预处理方式,但是在预处理完成后,通常可以使用通用的方法对这些数据进行分析,如分类和网络分析.从研究问题的角度讨论了多种分别用于解答不同复杂度问题的研究方法.这些由简单到复杂的问题包括关联性检测、归类分析、构建分类器、获得网络连接和动态模型构建.

To achieve precision medicine, collecting and analysing various big data are needed to quantify individual patients. This paper first discusses the need of using data from molecular level to pathway level and also incorporating medical imaging data. Differ- ent preprocessing methods should be developed for different data type, while some post- processing steps for various data types, such as classification and network analysis, can be done by a generalized approach. From the perspective of research questions, this paper then studies methods for answering five typical questions from simple to complex. These questions are detecting associations, identifying groups, constructing classifiers, derivingconnectivity and building dynamic models.