A Novel Knowledge Representation Framework for the Statistical Validation of Quantitative Imaging Biomarkers.
Quantitative imaging biomarkers are of particular interest in drug development for their potential to accelerate the drug development pipeline. The lack of consensus methods and carefully characterized performance hampers the widespread availability of these quantitative measures. A framework to sup...
| Publicado en: | Journal of Digital Imaging Vol. 26; no. 4; pp. 614 - 630 |
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| Autores principales: | , , , , , |
| Formato: | pictorial 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=104190868&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104190868 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: 104190868 88934664 10.1007/s10278-013-9598-3 NLM23546775 PMC3705009 104190868 ppf: 614 ppct: 16 formats: fmt: @attributes: type: P tig: atl: A Novel Knowledge Representation Framework for the Statistical Validation of Quantitative Imaging Biomarkers. aug: au: Buckler, Andrew Paik, David Ouellette, Matt Danagoulian, Jovanna Wernsing, Gary Suzek, Baris affil: BBMSC, 225 Main Street, Suite 15 Wenham 01984 USA sug: subj: Biological Markers Diagnostic Imaging Standards Vocabulary, Controlled Knowledge Expert Systems Medical Informatics Models, Statistical World Wide Web Applications ab: Quantitative imaging biomarkers are of particular interest in drug development for their potential to accelerate the drug development pipeline. The lack of consensus methods and carefully characterized performance hampers the widespread availability of these quantitative measures. A framework to support collaborative work on quantitative imaging biomarkers would entail advanced statistical techniques, the development of controlled vocabularies, and a service-oriented architecture for processing large image archives. Until now, this framework has not been developed. With the availability of tools for automatic ontology-based annotation of datasets, coupled with image archives, and a means for batch selection and processing of image and clinical data, imaging will go through a similar increase in capability analogous to what advanced genetic profiling techniques have brought to molecular biology. We report on our current progress on developing an informatics infrastructure to store, query, and retrieve imaging biomarker data across a wide range of resources in a semantically meaningful way that facilitates the collaborative development and validation of potential imaging biomarkers by many stakeholders. Specifically, we describe the semantic components of our system, QI-Bench, that are used to specify and support experimental activities for statistical validation in quantitative imaging pubtype: Academic Journal doctype: pictorial tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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