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Details of Grant 

EPSRC Reference: GR/R86041/01
Title: Hybrid Artificial Intelligence Ensemble for Early Detection of Osteoporosis
Principal Investigator: Wang, Dr W
Other Investigators:
Rae, Dr S
Researcher Co-Investigators:
Project Partners:
Department: Computing Sciences
Organisation: University of East Anglia
Scheme: Standard Research (Pre-FEC)
Starts: 01 October 2002 Ends: 30 September 2005 Value (£): 129,133
EPSRC Research Topic Classifications:
Artificial Intelligence Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:  
Summary on Grant Application Form
The osteoporosis disease has been identified by WHO as a global silent epidemic which affects 1 in 3 women. There is currently no cure but it could be effectively prevented. Early detection of the disease is key to prevention, and forms the basis of our research. The principal goal of the proposed research is to investigate a methodology of constructing hybrid ensemble of data mining techniques for identifying salient risk factors and then to develop an artificial intelligence system to assist early detection. The proposed project is viewed as an extension of our current and past work on both the chosen technologies and their application for the osteoporosis problem.The proposed investigations will explore reasoning techniques such as, automatically induced decision trees and neural networks, as well as some conventional techniques commonly applied in medical fields, such as correlation, logistic regression and probabilistic analysis. A hybrid ensemble pursues an effective combination of various approaches in order to utilise the strengths of each individual technique and compensate for their weaknesses and therefore produce 'optimal' decisions. The focus of this proposal is to investigate and develop such a system to improve identification of patients at potential risk of developing osteoporosis as early as possible.
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