Harvest: an open platform for developing web-based biomedical data discovery and reporting applications.
Biomedical researchers share a common challenge of making complex data understandable and accessible as they seek inherent relationships between attributes in disparate data types. Data discovery in this context is limited by a lack of query systems that efficiently show relationships between indivi...
| Publicado en: | Journal of the American Medical Informatics Association Vol. 21; no. 2; pp. 379 - 384 |
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| Autores principales: | , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Oxford University Press / USA
Mar2014
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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=104021490&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104021490 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10675027 FZ9 jtl: Journal of the American Medical Informatics Association issn: 10675027 maglogo: N pubinfo: dt: Mar2014 vid: 21 iid: 2 pid: 622 pub: Oxford University Press / USA artinfo: ui: 104021490 NLM24131510 2012470479 10.1136/amiajnl-2013-001825 NLM24131510 PMC3932456 104021490 ppf: 379 ppct: 5 formats: tig: atl: Harvest: an open platform for developing web-based biomedical data discovery and reporting applications. aug: au: Pennington, Jeffrey W Ruth, Byron Italia, Michael J Miller, Jeffrey Wrazien, Stacey Loutrel, Jennifer G Crenshaw, E Bryan White, Peter S affil: Center for Biomedical Informatics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA. sug: subj: Research, Medical Bioinformatics Methods Management Information Systems Resource Databases Human Internet Quality of Health Care Product Acquisition Software ab: Biomedical researchers share a common challenge of making complex data understandable and accessible as they seek inherent relationships between attributes in disparate data types. Data discovery in this context is limited by a lack of query systems that efficiently show relationships between individual variables, but without the need to navigate underlying data models. We have addressed this need by developing Harvest, an open-source framework of modular components, and using it for the rapid development and deployment of custom data discovery software applications. Harvest incorporates visualizations of highly dimensional data in a web-based interface that promotes rapid exploration and export of any type of biomedical information, without exposing researchers to underlying data models. We evaluated Harvest with two cases: clinical data from pediatric cardiology and demonstration data from the OpenMRS project. Harvest's architecture and public open-source code offer a set of rapid application development tools to build data discovery applications for domain-specific biomedical data repositories. All resources, including the OpenMRS demonstration, can be found at http://harvest.research.chop.edu. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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