A Multiagent System for Dynamic Data Aggregation in Medical Research.
The collection of medical data for research purposes is a challenging and long-lasting process. In an effort to accelerate and facilitate this process we propose a new framework for dynamic aggregation of medical data from distributed sources. We use agent-based coordination between medical and rese...
| Publicado en: | BioMed Research International Vol. 2016; pp. 1 - 13 |
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| Autores principales: | , , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
11/16/2016
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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=119493447&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 119493447 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 11/16/2016 vid: 2016 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 119493447 119493447 119493447 10.1155/2016/9027457 119493447 ppf: 1 ppct: 12 formats: fmt: @attributes: type: P tig: atl: A Multiagent System for Dynamic Data Aggregation in Medical Research. aug: au: Dubovitskaya, Alevtina Urovi, Visara Barba, Imanol Aberer, Karl Schumacher, Michael Ignaz affil: Applied Intelligent Systems Laboratory, HES-SO VS, Sierre, Switzerland sug: subj: Research, Medical Data Management Database Design Database Construction Resource Databases, Health Data Security Privacy and Confidentiality Simulations Comparative Studies Funding Source ab: The collection of medical data for research purposes is a challenging and long-lasting process. In an effort to accelerate and facilitate this process we propose a new framework for dynamic aggregation of medical data from distributed sources. We use agent-based coordination between medical and research institutions. Our system employs principles of peer-to-peer network organization and coordination models to search over already constructed distributed databases and to identify the potential contributors when a new database has to be built. Our framework takes into account both the requirements of a research study and current data availability. This leads to better definition of database characteristics such as schema, content, and privacy parameters. We show that this approach enables a more efficient way to collect data for medical research. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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