Semantic-based data integration model applied to heterogeneous medical information system

Shi, Yunmei; Liu, Xuhong; Xu, Yabin; Ji, Zhenyan

doi:10.1109/iccae.2010.5451697

Cited by 7 publications

(4 citation statements)

References 10 publications

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“…Additionally, there are a number of studies and research related to heterogeneous data integration based on, for instance, XML ( Fengguang, Xie, & Liqun, 2009 ) ( Su, Fan, & Li, 2010 ) ( Lin, 2009 ), Lucene and XQuery ( Tianyuan, Meina, & Xiaoqi, 2010 ), and OGSA-DAI ( Gao & Xiao, 2013 ). In the same way, heterogeneous data integration has applications to many areas, such as Livestock Products Traceability ( Chen & Liu, 2009 ), safety production ( Han, Tian, & Wu, 2009 ), management information systems ( Hailing & Yujie, 2012 ), medical information ( Shi, Liu, Xu, & Ji, 2010 ), and web environments ( Fan & Gui, 2007 ).…”

Section: Bibliographical Reviewmentioning

confidence: 99%

Heterogeneous data source integration for smart grid ecosystems based on metadata mining

Guerrero

Garca

Personal

et al. 2017

Expert Systems with Applications

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Section: Bibliographical Reviewmentioning

confidence: 99%

Heterogeneous data source integration for smart grid ecosystems based on metadata mining

Guerrero

Garca

Personal

et al. 2017

Expert Systems with Applications

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“…Semantic Web technologies are ideally suited to model such complex systems; In contrast to static terminology structures used for knowledge reference, semantic ontologies allow to describe at the taxonomy level the concepts and sophisticated relationships between the concepts (subsumption, cardinality, jointness, etc. ), thus allowing for knowledge inference and reasoning [11]. Semantic knowledgebases are also inherently extensible [12] compared to traditional RDBS, which is again very useful for the everevolving medical domains.…”

Section: Motivationmentioning

confidence: 99%

Semantic-based decision support for remote care of Dementia patients

Osman

Lotfi

Langensiepen

et al. 2014

2014 IEEE Symposium on Intelligent Agents (IA)

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Abstract-This paper investigates the challenges in developing a semantic-based Dementia Care Decision Support System based on the non-intrusive monitoring of the patient's behaviour. Semantic-based approaches are well suited for modelling context-aware scenarios similar to Dementia care systems, where the patient's dynamic behaviour observations (occupants movement, equipment use) need to be analysed against the semantic knowledge about the patient's condition (illness history, medical advice, known symptoms) in an integrated knowledgebase. However, our research findings establish that the ability of semantic technologies to reason upon the complex interrelated events emanating from the behaviour monitoring sensors to infer knowledge assisting medical advice represents a major challenge. We attempt to address this problem by introducing a new approach that relies on propositional calculus modelling to segregate complex events that are amenable for semantic reasoning from events that require pre-processing outside the semantic engine before they can be reasoned upon. The event pre-processing activity also controls the timing of triggering the reasoning process in order to further improve the efficiency of the inference process. Using regression analysis, we evaluate the response-time as the number of monitored patients increases and conclude that the incurred overhead on the response time of the prototype decision support systems remains tolerable.

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“…According to [2], there are three different levels of interoperability in information: semantic interoperability, structural interoperability and syntactic interoperability.…”

Section: Introductionmentioning

confidence: 99%

Interoperability of healthcare information systems

Hammami¹,

Bellâaj²,

Kacem³

2014

The 2014 International Symposium on Networks, Computers and Communications

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Medical information systems are in perpetual evolution which makes them different from each other in each hospital. These different systems compose a heterogeneous, distributed system with high complexity. Thus interoperability of medical information systems is one of the main challenges of the IT society. Semantic interoperability in healthcare is especially important when all the varying types of data need to interact.A lot of works tried to solve even partially this problem of interoperability. This paper highlights the most relevant of them and presents a comparative study between new technologies and research trends to resolve heterogeneity issues of medical information systems.

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Semantic-based data integration model applied to heterogeneous medical information system

Cited by 7 publications

References 10 publications

Heterogeneous data source integration for smart grid ecosystems based on metadata mining

Heterogeneous data source integration for smart grid ecosystems based on metadata mining

Semantic-based decision support for remote care of Dementia patients

Interoperability of healthcare information systems

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