Linked Life Data

18827457

Source:http://linkedlifedata.com/resource/pubmed/id/18827457

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2008-10-1
pubmed:abstractText
Ontological engineering is one of the most challenging topics in biomedical informatics because of its key role in integrating the heterogeneous database used by biomedical information services. Ontology can translate concepts and their real-world relationships into expressions that can be processed by computer programs or web services, providing a unique taxonomic frame to describe a pathway for extracting, processing, storing, and retrieving information. In developing clinical functional neuroimaging, which requires the integration of heterogeneous information derived from multimodal measurement of the brain, these features will be indispensable. Neuroimaging ontology is remarkable in that it requires detailed description of the hypothesis, the paradigm employed, and a scheme for data generation. Neuroimaging modalities, such as functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), electroencephalography (EEG), and near infrared spectroscopy (NIRS), share similar application purposes, imaging protocol, analyzing methods, and data structure; semantic gaps that remain among the modalities will be bridged as ontology develops. High-performance, global resource information database (GRID) computing and the applications organized as service-oriented computing (SOC) will support the heavy processing to integrate the heterogeneous neuroimaging system. We have been developing such a distributed intelligent neuroimaging system for real-time fMRI analysis, called BAXGRID, and a neuroimaging database. The fMRI ontology of this system will be integrated with established medical ontologies, such as the Unified Medical Language System (UMLS).
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1347-3182
pubmed:author
pubmed:issnType
Print
pubmed:volume
7
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
141-55
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Ontology for FMRI as a biomedical informatics method.
pubmed:affiliation
Functional Brain Imaging Lab, Department of Gerontechnology, National Center for Geriatrics and Gerontology, Aichi, Japan. toshi@nils.go.jp
pubmed:publicationType
Journal Article, Review, Research Support, Non-U.S. Gov't