A data gathering framework to collect Type 2 diabetes patients data

A. Dagliati, L. Sacchi, Mauro Bucalo, D. Segagni, K. Zarkogianni, A. Martínez-Millana, J. Cancela, Francesco Sambo, G. Fico, Maria Teresa Meneu Barreira, C. Cerra, K. Nikita, C. Cobelli, L. Chiovato, M. Arredondo, R. Bellazzi
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引用次数: 13

Abstract

In this work, we present a framework implemented within the EU project MOSAIC, funded under the FP7 framework, to gather Type 2 Diabetes (T2D) patients' data coming from three European hospitals and a local health care agency. A subset of the MOSAIC activities is centered on the development of Temporal Data Mining models to identify relevant clinical pathways in patients' histories and will in particular benefit from the data coming from the medical centers involved in the project. To best exploit this repository, the need for creating a common and sharable data model becomes immediately apparent. This model is the main subject of this paper. The proposed approach relies on the Informatics for Integrating Biology and the Bedside (i2b2) and the Shared Health Research Information Network (SHRINE) open source software tools. It provides an integrated research setting to merge clinical and environmental data that will enable obtaining a broader vision of individual patients' histories, which will be then mined with multivariate models to identify relevant clinical pathways.
收集2型糖尿病患者数据的数据收集框架
在这项工作中,我们提出了一个在欧盟项目MOSAIC内实施的框架,该项目由FP7框架资助,用于收集来自三家欧洲医院和一家当地卫生保健机构的2型糖尿病(T2D)患者数据。MOSAIC活动的一个子集集中于开发时间数据挖掘模型,以确定患者病史中的相关临床路径,并将特别受益于来自参与该项目的医疗中心的数据。为了最好地利用这个存储库,创建一个公共和可共享的数据模型的需求立即变得明显起来。该模型是本文的主要研究对象。所提出的方法依赖于集成生物学和床边信息学(i2b2)和共享健康研究信息网络(SHRINE)开源软件工具。它提供了一个整合的研究环境,将临床和环境数据合并在一起,从而能够更广泛地了解个体患者的病史,然后将其与多变量模型一起挖掘,以确定相关的临床途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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