150 research outputs found
The de novo FAIRification process of a registry for vascular anomalies
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A Framework for eHealth Interoperability Management
Reliable and secure access to and sharing of medical data can help patients practice self-care, promote patient engagement and improve their communication with healthcare professionals. This requires overcoming several interoperability, usability, ethics, security, and regulatory issues. The existence of a common interoperability framework can accelerate digital transformation in support of disease specific solutions. This paper presents a useful and relevant interoperability management framework with the potential to improve the quality of life and better control costs for the development and provision of electronic health services to individuals, within a coordinated care environment, under a local, regional, national, or cross-border setting
Foundations Of Service Science Technology And Architecture
This paper concludes the conspectus of Service Science for academicians and practitioners. It follows the two previous papers, entitled Foundations of Service Science: Concepts and Facilities and Foundations of Service Science: Management and Business, with the express purpose of defining the scope of the discipline. An eclectic background in service technology and service architecture is required to fully explore the research potential of a science based on services. This paper reviews the technical concepts needed to apply the concepts that have previously been introduced
Towards Interoperability in E-health Systems: a three-dimensional approach based on standards and semantics
Proceedings of: HEALTHINF 2009 (International Conference on Helath Informatics), Porto (Portugal), January 14-17, 2009, is part of BIOSTEC (Intemational Joint Conference on Biomedical Engineering Systems and Technologies)The interoperability problem in eHealth can only be addressed by mean of combining standards and technology. However, these alone do not suffice. An appropiate framework that articulates such combination is required. In this paper, we adopt a three-dimensional (information, conference and inference) approach for such framework, based on OWL as formal language for terminological and ontological health resources, SNOMED CT as lexical backbone for all such resources, and the standard CEN 13606 for representing EHRs. Based on tha framewok, we propose a novel form for creating and supporting networks of clinical terminologies. Additionally, we propose a number of software modules to semantically process and exploit EHRs, including NLP-based search and inference, wich can support medical applications in heterogeneous and distributed eHealth systems.This work has been funded as part of the Spanish nationally funded projects ISSE (FIT-350300-2007-75) and CISEP (FIT-350301-2007-18). We also acknowledge IST-2005-027595 EU project NeO
A FRAMEWORK FOR BIOPROFILE ANALYSIS OVER GRID
An important trend in modern medicine is towards individualisation of healthcare to tailor
care to the needs of the individual. This makes it possible, for example, to personalise
diagnosis and treatment to improve outcome. However, the benefits of this can only be fully
realised if healthcare and ICT resources are exploited (e.g. to provide access to relevant data,
analysis algorithms, knowledge and expertise). Potentially, grid can play an important role
in this by allowing sharing of resources and expertise to improve the quality of care. The
integration of grid and the new concept of bioprofile represents a new topic in the healthgrid
for individualisation of healthcare.
A bioprofile represents a personal dynamic "fingerprint" that fuses together a person's
current and past bio-history, biopatterns and prognosis. It combines not just data, but also
analysis and predictions of future or likely susceptibility to disease, such as brain diseases
and cancer. The creation and use of bioprofile require the support of a number of healthcare
and ICT technologies and techniques, such as medical imaging and electrophysiology and
related facilities, analysis tools, data storage and computation clusters. The need to share
clinical data, storage and computation resources between different bioprofile centres creates
not only local problems, but also global problems.
Existing ICT technologies are inappropriate for bioprofiling because of the difficulties in the
use and management of heterogeneous IT resources at different bioprofile centres. Grid as an
emerging resource sharing concept fulfils the needs of bioprofile in several aspects, including
discovery, access, monitoring and allocation of distributed bioprofile databases, computation
resoiuces, bioprofile knowledge bases, etc. However, the challenge of how to integrate the
grid and bioprofile technologies together in order to offer an advanced distributed bioprofile
environment to support individualized healthcare remains.
The aim of this project is to develop a framework for one of the key meta-level bioprofile
applications: bioprofile analysis over grid to support individualised healthcare. Bioprofile
analysis is a critical part of bioprofiling (i.e. the creation, use and update of bioprofiles).
Analysis makes it possible, for example, to extract markers from data for diagnosis and to
assess individual's health status. The framework provides a basis for a "grid-based" solution
to the challenge of "distributed bioprofile analysis" in bioprofiling. The main contributions
of the thesis are fourfold:
A. An architecture for bioprofile analysis over grid. The design of a suitable aichitecture
is fundamental to the development of any ICT systems. The architecture creates a
meaiis for categorisation, determination and organisation of core grid components to
support the development and use of grid for bioprofile analysis;
B. A service model for bioprofile analysis over grid. The service model proposes a
service design principle, a service architecture for bioprofile analysis over grid, and
a distributed EEG analysis service model. The service design principle addresses
the main service design considerations behind the service model, in the aspects of
usability, flexibility, extensibility, reusability, etc. The service architecture identifies
the main categories of services and outlines an approach in organising services to
realise certain functionalities required by distributed bioprofile analysis applications.
The EEG analysis service model demonstrates the utilisation and development of
services to enable bioprofile analysis over grid;
C. Two grid test-beds and a practical implementation of EEG analysis over grid. The two
grid test-beds: the BIOPATTERN grid and PlymGRID are built based on existing
grid middleware tools. They provide essential experimental platforms for research in
bioprofiling over grid. The work here demonstrates how resources, grid middleware
and services can be utilised, organised and implemented to support distributed EEG
analysis for early detection of dementia. The distributed Electroencephalography
(EEG) analysis environment can be used to support a variety of research activities in
EEG analysis;
D. A scheme for organising multiple (heterogeneous) descriptions of individual grid
entities for knowledge representation of grid. The scheme solves the compatibility
and adaptability problems in managing heterogeneous descriptions (i.e. descriptions
using different languages and schemas/ontologies) for collaborated representation of
a grid environment in different scales. It underpins the concept of bioprofile analysis
over grid in the aspect of knowledge-based global coordination between components
of bioprofile analysis over grid
Serviços de integração de dados para aplicações biomédicas
Doutoramento em Informática (MAP-i)In the last decades, the field of biomedical science has fostered
unprecedented scientific advances. Research is stimulated by the
constant evolution of information technology, delivering novel and
diverse bioinformatics tools. Nevertheless, the proliferation of new and
disconnected solutions has resulted in massive amounts of resources
spread over heterogeneous and distributed platforms. Distinct
data types and formats are generated and stored in miscellaneous
repositories posing data interoperability challenges and delays in
discoveries. Data sharing and integrated access to these resources
are key features for successful knowledge extraction.
In this context, this thesis makes contributions towards accelerating
the semantic integration, linkage and reuse of biomedical resources.
The first contribution addresses the connection of distributed and
heterogeneous registries. The proposed methodology creates a
holistic view over the different registries, supporting semantic
data representation, integrated access and querying. The second
contribution addresses the integration of heterogeneous information
across scientific research, aiming to enable adequate data-sharing
services. The third contribution presents a modular architecture to
support the extraction and integration of textual information, enabling
the full exploitation of curated data. The last contribution lies
in providing a platform to accelerate the deployment of enhanced
semantic information systems. All the proposed solutions were
deployed and validated in the scope of rare diseases.Nas últimas décadas, o campo das ciências biomédicas proporcionou
grandes avanços científicos estimulados pela constante evolução das
tecnologias de informação. A criação de diversas ferramentas na
área da bioinformática e a falta de integração entre novas soluções
resultou em enormes quantidades de dados distribuídos por diferentes
plataformas. Dados de diferentes tipos e formatos são gerados
e armazenados em vários repositórios, o que origina problemas de
interoperabilidade e atrasa a investigação. A partilha de informação
e o acesso integrado a esses recursos são características fundamentais
para a extração bem sucedida do conhecimento científico.
Nesta medida, esta tese fornece contribuições para acelerar a
integração, ligação e reutilização semântica de dados biomédicos. A
primeira contribuição aborda a interconexão de registos distribuídos e
heterogéneos. A metodologia proposta cria uma visão holística sobre
os diferentes registos, suportando a representação semântica de dados
e o acesso integrado. A segunda contribuição aborda a integração
de diversos dados para investigações científicas, com o objetivo de
suportar serviços interoperáveis para a partilha de informação. O
terceiro contributo apresenta uma arquitetura modular que apoia a
extração e integração de informações textuais, permitindo a exploração
destes dados. A última contribuição consiste numa plataforma web
para acelerar a criação de sistemas de informação semânticos. Todas
as soluções propostas foram validadas no âmbito das doenças raras
Mutable Class Design Pattern
The dissertation proposes, presents and analyzes a new design pattern, the Mutable Class pattern, to support the processing of large-scale heterogeneous data models with multiple families of algorithms. Handling data-algorithm associations represents an important topic across a variety of application domains. As a result, it has been addressed by multiple approaches, including the Visitor pattern and the aspect-oriented programming (AOP) paradigm. Existing solutions, however, bring additional constraints and issues. For example, the Visitor pattern freezes the class hierarchies of application models and the AOP-based projects, such as Spring AOP, introduce significant overhead for processing large-scale models with fine-grain objects. The Mutable Class pattern addresses the limitations of these solutions by providing an alternative approach designed after the Class model of the UML specification. Technically, it extends a data model class with a class mutator supporting the interchangeability of operations.
Design patterns represent reusable solutions to recurring problems. According to the design pattern methodology, the definition of these solutions encompasses multiple topics, such as the problem and applicability, structure, collaborations among participants, consequences, implementation aspects, and relation with other patterns. The dissertation provides a formal description of the Mutable Class pattern for processing heterogeneous tree-based models and elaborates on it with a comprehensive analysis in the context of several applications and alternative solutions. Particularly, the commonality of the problem and reusability of this approach is demonstrated and evaluated within two application domains: computational accelerator physics and compiler construction. Furthermore, as a core part of the Unified Accelerator Library (UAL) framework, the scalability boundary of the pattern has been challenged and explored with different categories of application architectures and computational infrastructures including distributed three-tier systems.
The Mutable Class pattern targets a common problem arising from software engineering: the evolution of type systems and associated algorithms. Future research includes applying this design pattern in other contexts, such as heterogeneous information networks and large-scale processing platforms, and examining variations and alternative design patterns for solving related classes of problems
A standards-based ICT framework to enable a service-oriented approach to clinical decision support
This research provides evidence that standards based Clinical Decision Support (CDS)
at the point of care is an essential ingredient of electronic healthcare service delivery. A
Service Oriented Architecture (SOA) based solution is explored, that serves as a task
management system to coordinate complex distributed and disparate IT systems,
processes and resources (human and computer) to provide standards based CDS.
This research offers a solution to the challenges in implementing computerised CDS such
as integration with heterogeneous legacy systems. Reuse of components and services to
reduce costs and save time. The benefits of a sharable CDS service that can be reused by
different healthcare practitioners to provide collaborative patient care is demonstrated.
This solution provides orchestration among different services by extracting data from
sources like patient databases, clinical knowledge bases and evidence-based clinical
guidelines (CGs) in order to facilitate multiple CDS requests coming from different
healthcare settings. This architecture aims to aid users at different levels of Healthcare
Delivery Organizations (HCOs) to maintain a CDS repository, along with monitoring and
managing services, thus enabling transparency.
The research employs the Design Science research methodology (DSRM) combined with
The Open Group Architecture Framework (TOGAF), an open source group initiative for
Enterprise Architecture Framework (EAF). DSRM’s iterative capability addresses the
rapidly evolving nature of workflows in healthcare. This SOA based solution uses
standards-based open source technologies and platforms, the latest healthcare standards
by HL7 and OMG, Decision Support Service (DSS) and Retrieve, Update Locate Service
(RLUS) standard. Combining business process management (BPM) technologies,
business rules with SOA ensures the HCO’s capability to manage its processes. This
architectural solution is evaluated by successfully implementing evidence based CGs at
the point of care in areas such as; a) Diagnostics (Chronic Obstructive Disease), b) Urgent
Referral (Lung Cancer), c) Genome testing and integration with CDS in screening
(Lynch’s syndrome). In addition to medical care, the CDS solution can benefit
organizational processes for collaborative care delivery by connecting patients,
physicians and other associated members. This framework facilitates integration of
different types of CDS ideal for the different healthcare processes, enabling sharable CDS
capabilities within and across organizations
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