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首页> 外文会议>International conference on social computing, behavioral-cultural modeling, and prediction >System-Subsystem Dependency Network for Integrating Multicomponent Data and Application to Health Sciences
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System-Subsystem Dependency Network for Integrating Multicomponent Data and Application to Health Sciences

机译：集成多成分数据的系统子系统依赖网络及其在健康科学中的应用

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摘要

Two features are commonly observed in large and complex systems. First, a system is made up of multiple subsystems. Second there exists fragmented data. A methodological challenge is to reconcile the potential parametric inconsistency across individually calibrated subsystems. This study aims to explore a novel approach, called system-subsystem dependency network, which is capable of integrating subsystems that have been individually calibrated using separate data sets. In this paper we compare several techniques for solving the methodological challenge. Additionally, we use data from a large-scale epidemiologic study as well as a large clinical trial to illustrate the solution to inconsistency of overlapping subsystems and the integration of data sets.
机译：在大型和复杂的系统中通常会观察到两个特征。首先，一个系统由多个子系统组成。其次，存在零散的数据。方法上的挑战是调和各个校准子系统之间潜在的参数不一致。这项研究旨在探索一种称为系统子系统依赖网络的新颖方法，该方法能够集成已使用单独的数据集进行单独校准的子系统。在本文中，我们比较了解决方法挑战的几种技术。此外，我们使用来自大规模流行病学研究以及大型临床试验的数据来说明解决重叠子系统不一致和数据集整合的解决方案。

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