Experiences of Engineering Grid-Based Medical Software
Objectives: Grid-based technologies are emerging as potential solutions for managing and collaborating distributed resources in the biomedical domain. Few examples exist, however, of successful implementations of Grid-enabled medical systems and even fewer have been deployed for evaluation in practi...
Gespeichert in:
Hauptverfasser: | , , , , , |
---|---|
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Objectives: Grid-based technologies are emerging as potential solutions for
managing and collaborating distributed resources in the biomedical domain. Few
examples exist, however, of successful implementations of Grid-enabled medical
systems and even fewer have been deployed for evaluation in practice. The
objective of this paper is to evaluate the use in clinical practice of a
Grid-based imaging prototype and to establish directions for engineering future
medical Grid developments and their subsequent deployment. Method: The
MammoGrid project has deployed a prototype system for clinicians using the Grid
as its information infrastructure. To assist in the specification of the system
requirements (and for the first time in healthgrid applications), use-case
modelling has been carried out in close collaboration with clinicians and
radiologists who had no prior experience of this modelling technique. A
critical qualitative and, where possible, quantitative analysis of the
MammoGrid prototype is presented leading to a set of recommendations from the
delivery of the first deployed Grid-based medical imaging application. Results:
We report critically on the application of software engineering techniques in
the specification and implementation of the MammoGrid project and show that
use-case modelling is a suitable vehicle for representing medical requirements
and for communicating effectively with the clinical community. This paper also
discusses the practical advantages and limitations of applying the Grid to
real-life clinical applications and presents the consequent lessons learned. |
---|---|
DOI: | 10.48550/arxiv.0707.0748 |