Health-e-Child: a grid platform for european paediatrics

Skaburskas, Konstantin; Estrella, Florida; Shade, John; Manset, David; Revillard, Jérôme; Ríos, Augusto Conte de los; Anjum, Ashiq; Branson, Andrew; Bloodsworth, Peter; Hauer, Tamás; McClatchey, Richard; Rogulin, Dmitry

doi:10.1088/1742-6596/119/8/082011

Cited by 5 publications

(4 citation statements)

References 2 publications

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“…The work presented in this paper has been mainly developed in the context of the European Health-e-Child (HeC) integrated project [ 31 , 32 ]. HeC aimed to develop an integrated health care platform to allow clinicians to access, analyze, evaluate, enhance and exchange integrated biomedical information focused on three pediatric domains: heart disorders, inflammatory disorders and brain tumors.…”

Section: Resultsmentioning

confidence: 99%

Exploring and linking biomedical resources through multidimensional semantic spaces

2012

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BackgroundThe semantic integration of biomedical resources is still a challenging issue which is required for effective information processing and data analysis. The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows disparate data formats and contents to be expressed under a common semantic space. In this paper, we propose a multidimensional representation for such a semantic space, where dimensions regard the different perspectives in biomedical research (e.g., population, disease, anatomy and protein/genes).ResultsThis paper presents a novel method for building multidimensional semantic spaces from semantically annotated biomedical data collections. This method consists of two main processes: knowledge and data normalization. The former one arranges the concepts provided by a reference knowledge resource (e.g., biomedical ontologies and thesauri) into a set of hierarchical dimensions for analysis purposes. The latter one reduces the annotation set associated to each collection item into a set of points of the multidimensional space. Additionally, we have developed a visual tool, called 3D-Browser, which implements OLAP-like operators over the generated multidimensional space. The method and the tool have been tested and evaluated in the context of the Health-e-Child (HeC) project. Automatic semantic annotation was applied to tag three collections of abstracts taken from PubMed, one for each target disease of the project, the Uniprot database, and the HeC patient record database. We adopted the UMLS Meta-thesaurus 2010AA as the reference knowledge resource.ConclusionsCurrent knowledge resources and semantic-aware technology make possible the integration of biomedical resources. Such an integration is performed through semantic annotation of the intended biomedical data resources. This paper shows how these annotations can be exploited for integration, exploration, and analysis tasks. Results over a real scenario demonstrate the viability and usefulness of the approach, as well as the quality of the generated multidimensional semantic spaces.

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Section: Resultsmentioning

confidence: 99%

Exploring and linking biomedical resources through multidimensional semantic spaces

2012

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“…The application scenario selected to develop our analysis framework is Biomedicine, in which vast and complex domain ontologies are being developed. In particular, we focus on the Health-e-Child integrated project (HeC) [137]. HeC was an European funded project that aimed at improving personalized healthcare in selected areas of paediatrics, particularly focusing on integrating and providing decision support tools for medical data across disciplines, modalities, and vertical levels such as molecular, organ, individual and population.…”

Section: Application Scenariomentioning

confidence: 99%

Scalable methods to analyze Semantic Web data

Romero

2016

AIC

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Semantic Web data is currently being heavily used as a data representation format in scientific communities, social networks, business companies, news portals and other domains. The irruption and availability of Semantic Web data is demanding new methods and tools to efficiently analyze such data and take advantage of the underlying semantics. Although there exist some applications that make use of Semantic Web data, advanced analytical tools are still lacking, preventing the user from exploiting the attached semantics.

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“…In this paper we adopt the application scenario of the Health-e-Child integrated project (HeC) [37], which aimed to provide a grid-based integrated data This scenario regards three main types of data sources: well standardized records coming from hospital information systems (e.g. HL7-conformant records), highly heterogeneous semi-structured clinical reports, and a variety of unstructured data such as DICOM files, ECG data, X-ray and ultrasonography images.…”

Section: Application Scenariomentioning

confidence: 99%

Building data warehouses with semantic web data

NebotVictoria

BerlangaRafael

2012

Decision Support Systems

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The Semantic Web (SW) deployment is now a realization and the amount of semantic annotations is ever increasing thanks to several initiatives that promote a change in the current Web towards the Web of Data, where the semantics of data become explicit through data representation formats and standards such as RDF/(S) and OWL. However, such initiatives have not yet been accompanied by efficient intelligent applications that can exploit the implicit semantics and thus, provide more insightful analysis. In this paper, we provide the means for efficiently analyzing and exploring large amounts of semantic data by combining the inference power from the annotation semantics with the analysis capabilities provided by OLAP-style aggregations, navigation, and reporting. We formally present how semantic data should be organized in a well-defined conceptual MD schema, so that sophisticated queries can be expressed and evaluated. Our proposal has been evaluated over a real biomedical scenario, which demonstrates the scalability and applicability of the proposed approach.

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Health-e-Child: a grid platform for european paediatrics

Cited by 5 publications

References 2 publications

Exploring and linking biomedical resources through multidimensional semantic spaces

Exploring and linking biomedical resources through multidimensional semantic spaces

Scalable methods to analyze Semantic Web data

Building data warehouses with semantic web data

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