Delivering a Lifelong Integrated Electronic Health Record Based on a Service Oriented Architecture

Katehakis, Dimitrios G.; Sfakianakis, Stelios; Kavlentakis, G.; Anthoulakis, Dimitrios; Tsiknakis, Manolis

doi:10.1109/titb.2006.889711

Cited by 49 publications

(29 citation statements)

References 3 publications

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“…Vertical integration: the aggregation of semantically similar data from multiple heterogeneous sources. For example, a 'virtual repository' that provides homogeneous access to clinical data that are stored and managed in databases across a regional health information network is reported in [16,17,18]. …”

Section: Heterogeneous Biomedical Database Integrationmentioning

confidence: 99%

Developing a European grid infrastructure for cancer research: vision, architecture, and services

Tsiknakis¹

2015

ecancer

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Life sciences are currently at the centre of an information revolution. The nature and amount of information now available opens up areas of research that were once in the realm of science fiction. During this information revolution, the data-gathering capabilities have greatly surpassed the data-analysis techniques. Data integration across heterogeneous data sources and data aggregation across different aspects of the biomedical spectrum, therefore, is at the centre of current biomedical and pharmaceutical R&D. This paper reports on original results from the ACGT integrated project, focusing on the design and development of a European Biomedical Grid infrastructure in support of multi-centric, post-genomic clinical trials (CTs) on cancer. Post-genomic CTs use multi-level clinical and genomic data and advanced computational analysis and visualization tools to test hypotheses in trying to identify the molecular reasons for a disease and the stratification of patients in terms of treatment.The paper provides a presentation of the needs of users involved in post-genomic CTs and presents indicative scenarios, which drive the requirements of the engineering phase of the project. Subsequently, the initial architecture specified by the project is presented, and its services are classified and discussed. A range of such key services, including the Master Ontology on sCancer, which lie at the heart of the integration architecture of the project, is presented. Special efforts have been taken to describe the methodological and technological framework of the project, enabling the creation of a legally compliant and trustworthy infrastructure. Finally, a short discussion of the forthcoming work is included, and the potential involvement of the cancer research community in further development or utilization of the infrastructure is described.

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Section: Heterogeneous Biomedical Database Integrationmentioning

confidence: 99%

Developing a European grid infrastructure for cancer research: vision, architecture, and services

Tsiknakis¹

2015

ecancer

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“…As a matter of fact, web services are recognized as an open and standardized way of achieving interoperation between different software applications, running on heterogeneous platforms and/or frameworks [15]. …”

Section: Related Workmentioning

confidence: 99%

ERMHAN: A Context-Aware Service Platform to Support Continuous Care Networks for Home-Based Assistance

Paganelli

Spinicci

Giuli

2008

International Journal of Telemedicine and Applications

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Continuous care models for chronic diseases pose several technology-oriented challenges for home-based continuous care, where assistance services rely on a close collaboration among different stakeholders such as health operators, patient relatives, and social community members. Here we describe Emilia Romagna Mobile Health Assistance Network (ERMHAN) a multichannel context-aware service platform designed to support care networks in cooperating and sharing information with the goal of improving patient quality of life. In order to meet extensibility and flexibility requirements, this platform has been developed through ontology-based context-aware computing and a service oriented approach. We also provide some preliminary results of performance analysis and user survey activity.

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“…The aggregation of semantically similar data from multiple heterogeneous sources. For example, a "virtual repository" that provides homogeneous access to clinical data that are stored and managed in databases across a regional health information network is reported in (Katehakis, 2007) and ( Lesch, 1997).…”

Section: Heterogeneous Biomedical Databases Integrationmentioning

confidence: 99%

A Semantic Grid Services Architecture in Support of Efficient Knowledge Discovery From Multilevel Clinical and Genomic Datasets

Tsiknakis

Sfakianakis

Rueping³

et al. 2008

Proceedings of the First International Conference on Health Informatics

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Abstract:This paper presents the architectural considerations of the Advancing Clinico-Genomic Trials on Cancer (ACGT) project aiming at delivering a European Biomedical Grid in support of efficient knowledge discovery in the context of post-genomic clinical trials on cancer. Our main research challenge in ACGT is the requirement to develop an infrastructure able to produce, use, and deploy knowledge as a basic element of advanced applications, which will mainly constitute a Biomedical Knowledge Grid. Our approach to offer semantic modelling of available services and data sources to support high level services and dynamic services for discovery and composition will be presented. In particular, ontologies and metadata are the basic elements through which Grid intelligence services can be developed, and the current achievmnets of the project in this domain will be discussed.

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Delivering a Lifelong Integrated Electronic Health Record Based on a Service Oriented Architecture

Cited by 49 publications

References 3 publications

Developing a European grid infrastructure for cancer research: vision, architecture, and services

Developing a European grid infrastructure for cancer research: vision, architecture, and services

ERMHAN: A Context-Aware Service Platform to Support Continuous Care Networks for Home-Based Assistance

A Semantic Grid Services Architecture in Support of Efficient Knowledge Discovery From Multilevel Clinical and Genomic Datasets

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