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https://doi.org/10.1109/sefm.2...
Article . 2007 . Peer-reviewed
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Model-driven architecture for cancer research

Authors: Radu Calinescu; Steve Harris; Jeremy Gibbons; Jim Davies; Igor Toujilov; Sylvia B. Nagl;

Model-driven architecture for cancer research

Abstract

It is a common phenomenon for research projects to collect and analyse valuable data using ad-hoc information systems. These costly-to-build systems are often composed of incompatible variants of the same modules, and record data in ways that prevent any meaningful result analysis across similar projects. We present a framework that uses a combination of formal methods, model-driven development and service-oriented architecture (SOA) technologies to automate the generation of data management systems for cancer clinical trial research, an area particularly affected by these problems. The SOA solution generated by the framework is based on an information model of a cancer clinical trial, and comprises components for both the collection and analysis of cancer research data, within and across clinical trial boundaries. While primarily targeted at cancer research, our approach is readily applicable to other areas for which a similar information model is available.

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Average
Top 10%
Top 10%
Green