A knowledge-rich distributed decision support framework: a case study for brain tumour diagnosis

David Dupplaw, Madalina Croitoru, Srinandan Dasmahapatra, Alex Gibb, Horacio Gonzalez-Velez, Miguel Lurgi, Bo Hu, Paul Lewis, Andrew Peet

Published: 28 Jul 2011, Last Modified: 05 Nov 2025The Knowledge Engineering ReviewEveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: The HealthAgents project aims to provide a decision support system for brain tumour diagnosis using a collaborative network of distributed agents. The goal is that through the aggregation of the small datasets available at individual hospitals much better decision support classifiers can be created and made available to the hospitals taking part. In this paper we describe the technicalities of the HealthAgents framework, in particular how the inter-operability of the various agents is managed using semantic web technologies. On the broad-scale the architecture is based around distributed data-mart agents that provide ontological access to hospitals’ underlying data that has been anonymised and processed from proprietary formats into a canonical format. Classifier producers have agents that gather the global data from participating hospitals such that classifiers can be created and deployed as agents. The design on a micro-scale has each agent built upon a generic layered-framework that provides the common agent program code, allowing rapid development of agents for the system. We believe our framework provides a well-engineered, agent-based approach to data-sharing in a medical context. It can provide a better basis on which to investigate the effectiveness of new classification techniques for brain tumour diagnosis.