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Related Experiment Videos

A generic model for Internet-accessed databases in epidemiology: a nutritional application.

F Hachem1, J Bellet, A Flory

  • 1Laboratoire d'Ingénierie des Systèmes d'Information, INSA Lyon, France. fhachem@laennec.univ-lyon1.fr

Studies in Health Technology and Informatics
|June 29, 1999
PubMed
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Web technology enables cost-effective information exchange and distributed medical applications. This study presents a generic, parameterizable epidemiological model optimized for collecting and processing nutritional data in renal failure studies.

Area of Science:

  • Medical Informatics
  • Epidemiology
  • Web Technology

Background:

  • Web technology facilitates information exchange across diverse platforms at no extra cost.
  • It enables access to geographically distributed databases, accelerating the development of distributed applications.
  • These capabilities make Web technology highly suitable for data-intensive, multi-user, and multiplatform medical applications.

Purpose of the Study:

  • To present a Web-based application for epidemiological studies.
  • To introduce a generic, parameterizable epidemiological model leveraging common epidemiological concepts.
  • To apply this model to optimize data collection and processing for a national renal failure study.

Main Methods:

  • Development of a Web-based application utilizing common epidemiological concepts.

Related Experiment Videos

  • Creation of a generic, parameterizable epidemiological model.
  • Application of the model for optimizing nutritional data collection and processing in a nationwide epidemiological study.

    • Main Results:

    • A functional Web-based application for epidemiological studies was developed.
    • The generic model proved parameterizable to meet specific study requirements.
    • The application successfully optimized the collection and processing of nutritional data for renal failure patients.

    Conclusions:

    • Web technology is a powerful tool for developing efficient medical applications, particularly in epidemiology.
    • A generic, parameterizable model enhances the adaptability of epidemiological studies.
    • The developed application effectively supports nationwide epidemiological research, specifically in nutritional data analysis for renal failure.