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An Agent Framework for Dynamic Health Data Aggregation for Research Purposes

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Karl Aberer, Michael Ignaz Schumacher, Alevtina Dubovitskaya
2015
conference papers

Abstract

This paper presents a model of a MAS framework for dynamic aggregation of population health data for research purposes. The contribution of the paper is twofold: First, it describes a MAS architecture that allows one to built on the fly anonymized databases from the distributed sources of data. Second, it shows how to improve the utility of the data with the growth of the database.

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https://infoscience.epfl.ch/entities/publication/253601e9-1446-4672-af6c-c3fa7352f903

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Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.

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