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XplOit:一个基于本体的数据集成平台,支持个性化医疗预测模型的开发。

XplOit: An Ontology-Based Data Integration Platform Supporting the Development of Predictive Models for Personalized Medicine.

作者信息

Weiler Gabriele, Schwarz Ulf, Rauch Jochen, Rohm Kerstin, Lehr Thorsten, Theobald Stefan, Kiefer Stephan, Götz Katharina, Och Katharina, Pfeifer Nico, Handl Lisa, Smola Sigrun, Ihle Matthias, Turki Amin T, Beelen Dietrich W, Rissland Jürgen, Bittenbring Jörg, Graf Norbert

机构信息

Fraunhofer Institute for Biomedical Engineering, St. Ingbert, Germany.

Institute for formal ontologies and medical information science.

出版信息

Stud Health Technol Inform. 2018;247:21-25.

Abstract

Predictive models can support physicians to tailor interventions and treatments to their individual patients based on their predicted response and risk of disease and help in this way to put personalized medicine into practice. In allogeneic stem cell transplantation risk assessment is to be enhanced in order to respond to emerging viral infections and transplantation reactions. However, to develop predictive models it is necessary to harmonize and integrate high amounts of heterogeneous medical data that is stored in different health information systems. Driven by the demand for predictive instruments in allogeneic stem cell transplantation we present in this paper an ontology-based platform that supports data owners and model developers to share and harmonize their data for model development respecting data privacy.

摘要

预测模型可以帮助医生根据个体患者的预测反应和疾病风险来定制干预措施和治疗方案,从而推动个性化医疗的实施。在异基因干细胞移植中,为应对新出现的病毒感染和移植反应,有必要加强风险评估。然而,要开发预测模型,就需要整合存储在不同健康信息系统中的大量异构医学数据。受异基因干细胞移植对预测工具的需求驱动,我们在本文中提出了一个基于本体的平台,该平台支持数据所有者和模型开发者在尊重数据隐私的前提下,为模型开发共享和整合他们的数据。

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