Details of Grant 

EPSRC Reference:	GR/R86782/01
Title:	Towards a Disciplined Approach to Integrating Decision Support Systems for Breast Cancer Care Activities
Principal Investigator:	Lisboa, Professor P
Other Investigators:	Taleb Bendiab, Professor A England, Dr D
Researcher Co-Investigators:
Project Partners:	Christie NHS Foundation Trust Liverpool Uni Hospitals NHS Fdn Trust
Department:	Computing and Mathematical Sciences
Organisation:	Liverpool John Moores University
Scheme:	Standard Research (Pre-FEC)
Starts:	14 October 2002	Ends:	13 January 2006	Value (£):	188,456
EPSRC Research Topic Classifications:	Human-Computer Interactions Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:
Summary on Grant Application Form
The evidence-based approach to the delivery of medical care has gained wide recognition within the healthcare community, advocating that decisionmaking should use current knowledge and clinical evidence from systematic research. In breast cancer care, there are currently few staging methods widespread use by clinicians, namely the Nottingham and Manchester staging systems. In which, however, there is no standard method to support oncologists' decision-making processes as to how and when to include new evidence, and how to validate emerging local patient data patterns again., other models and practices elsewhere. In a multi-disciplinary project settings involving; clinicians, statistitions, computer scientists and public health specialists, the proposed work will start by understanding the current decision-making practices before embarking into any systems' implementations the intended high-assurance decision support method. This will be evaluated using a set of small-scale controlled trials involving both patients and clinicians. The proposed method, unlike traditional decision-making techniques including multi-criterion will provide breast cancer clinicians and patier with a flexible decision framework adaptive to their decision practices yet allowing for evolutions of decision models, decision resources (data) and ott users concerns. This novel approach will provide important insights into the development of an integrated decision support infrastructure for highassurance decision activities. Which will directly contribute to one of the NHS R&D high-priority area of Medical Devices Directives for cancer patiant care.
Key Findings
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Organisation Website:	http://www.livjm.ac.uk