ONTOFUSION: Ontology-based integration of genomic and clinical databases

Pérez-Rey, David; Maojo, Víctor; García-Remesal, Miguel; Alonso-Calvo, Raúl; Billhardt, Holger; Martín-Sánchez, Fernando; Sousa, A.

doi:10.1016/j.compbiomed.2005.02.004

Cited by 89 publications

(52 citation statements)

References 25 publications

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“…This approach extends previous work on our group in ontology-based datábase integration of structured [2] and un structured sources [10], [8] and in image processing [5], [6].…”

Section: Introductionsupporting

confidence: 56%

Cloud Computing Service for Managing Large Medical Image Data-Sets Using Balanced Collaborative Agents

Alonso-Calvo

Crespo

Maojo

et al. 2011

Advances in Intelligent and Soft Computing

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Abstract. Managing large medical image coltections is an increasingiy demanding important issue in many hospitals and other medica) settings. A huge amount of this informaüon is daily generated, which requires robust and agüe systems. In this paper we present a distributed multi-agent system capable of managing very large medical image dataseis. In this approach, agents extract low-Ievel informaüon from ímages and store them in a data structure impiemented in a relational datábase. The data structure can also store semantic información related to images and particular regions. A distinctive aspect of our work is that a single image can be divided so that the resultant sub-images can be stored and managed separately by different agents to improve performance in data accessing and processing. The system also offers the possibüity of applying some region-based operations and filters on images, facilitating image classification. These operations can be performed directly on data structures in the datábase.

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“…This approach extends previous work on our group in ontology-based datábase integration of structured [2] and un structured sources [10], [8] and in image processing [5], [6].…”

Section: Introductionsupporting

confidence: 56%

Cloud Computing Service for Managing Large Medical Image Data-Sets Using Balanced Collaborative Agents

Alonso-Calvo

Crespo

Maojo

et al. 2011

Advances in Intelligent and Soft Computing

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“…Recently, several approaches to integrating medical and bioinformatics public databases have been ontology based (e.g. ONTOFUSION [5]). However, new issues and challenges arise from the introduction of domain ontologies when integrating information sources.…”

Section: Issues In Biomedical Data Integrationmentioning

confidence: 99%

The Management and Integration of Biomedical Knowledge: Application in the Health-e-Child Project (Position Paper)

Jiménez-Ruiz

Berlanga

Sanz

et al. 2006

On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshops

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Abstract. The Health-e-Child project aims to develop an integrated healthcare platform for European paediatrics. In order to achieve a comprehensive view of children's health, a complex integration of biomedical data, information, and knowledge is necessary. Ontologies will be used to formally define this domain knowledge and will form the basis for the medical knowledge management system. This paper introduces an innovative methodology for the vertical integration of biomedical knowledge. This approach will be largely cliniciancentered and will enable the definition of ontology fragments, connections between them (semantic bridges) and enriched ontology fragments (views). The strategy for the specification and capture of fragments, bridges and views is outlined with preliminary examples demonstrated in the collection of biomedical information from hospital databases, biomedical ontologies, and biomedical public databases.

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“…Other works deal with integration issues, for instance in [15] an OWL ontology is developed to integrate specific medical documents (CCD) authors focus on, whereas in [16] a complete method for ontology based schema and data integration for clinical and genomic databases is presented. Our goal is to provide a tool for extracting and integrating any (neither specific nor structured) medical information without creating a new ontology (rather, exploiting existing ones).…”

Section: Introductionmentioning

confidence: 99%

Multisource agent-based healthcare data gathering

Carchiolo

Longheu

Malgeri

et al. 2015

Annals of Computer Science and Information Systems

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Abstract-The number and type of digital sources storing healthcare data is increasing more and more, rising the problem of collecting actually dispersed information about a single patient. In this paper we propose an agent-based system to support integration of health-related data extracted from both structured (HIS) and semi-structured (websites and social networks) sources. Integrated data are exported in HL7 format to finally feed personal health record (PHR).

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ONTOFUSION: Ontology-based integration of genomic and clinical databases

Cited by 89 publications

References 25 publications

Cloud Computing Service for Managing Large Medical Image Data-Sets Using Balanced Collaborative Agents

Cloud Computing Service for Managing Large Medical Image Data-Sets Using Balanced Collaborative Agents

The Management and Integration of Biomedical Knowledge: Application in the Health-e-Child Project (Position Paper)

Multisource agent-based healthcare data gathering

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