Quantitative Imaging Biomarker Ontology (QIBO) for Knowledge Representation of Biomedical Imaging Biomarkers...[corrected] [published erratum appears in J DIGIT IMAGING 2013; 26(4):642]
A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. Howeve...
| Publicado en: | Journal of Digital Imaging Vol. 26; no. 4; pp. 630 - 642 |
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| Autores principales: | , , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104190853&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104190853 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Aug2013 vid: 26 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104190853 88934648 10.1007/s10278-013-9599-2 NLM23589184 PMC3705004 104190853 ppf: 630 ppct: 12 formats: fmt: @attributes: type: P tig: atl: Quantitative Imaging Biomarker Ontology (QIBO) for Knowledge Representation of Biomedical Imaging Biomarkers...[corrected] [published erratum appears in J DIGIT IMAGING 2013; 26(4):642] aug: au: Buckler, Andrew Ouellette, M. Danagoulian, J. Wernsing, G. Liu, Tiffany Savig, Erica Suzek, Baris Rubin, Daniel Paik, David affil: BBMSC, 225 Main Street, Suite 15 Wenham 01984 USA sug: subj: Biological Markers Diagnostic Imaging Knowledge Radiography Trends Vocabulary, Controlled Classification Funding Source Human Information Retrieval Medical Informatics Prospective Studies Semantics ab: A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. However, quantitative imaging biomarker data and knowledge are not standardized, representing a critical barrier to accumulating medical knowledge based on quantitative imaging data. We use an ontology to represent, integrate, and harmonize heterogeneous knowledge across the domain of imaging biomarkers. This advances the goal of developing applications to (1) improve precision and recall of storage and retrieval of quantitative imaging-related data using standardized terminology; (2) streamline the discovery and development of novel imaging biomarkers by normalizing knowledge across heterogeneous resources; (3) effectively annotate imaging experiments thus aiding comprehension, re-use, and reproducibility; and (4) provide validation frameworks through rigorous specification as a basis for testable hypotheses and compliance tests. We have developed the Quantitative Imaging Biomarker Ontology (QIBO), which currently consists of 488 terms spanning the following upper classes: experimental subject, biological intervention, imaging agent, imaging instrument, image post-processing algorithm, biological target, indicated biology, and biomarker application. We have demonstrated that QIBO can be used to annotate imaging experiments with standardized terms in the ontology and to generate hypotheses for novel imaging biomarker-disease associations. Our results established the utility of QIBO in enabling integrated analysis of quantitative imaging data. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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