Abstract.
In this paper a Decision Support System Architecture is proposed for the heart sound diagnosis problem, and in general for complex medical diagnosis problems. It is based on the division of a complex diagnostic problem into simpler sub-problems; each of them is handled by a specialized decision tree. This Multiple Decision Trees Architecture in general consists of a network of detection decision trees and arbitration decision trees, and can also incorporate other classification methods as well (e.g. patterns recognition, neural networks, etc.). The initial motivation for developing this Multiple Decision Trees Architecture has been the problem of differentiation among Opening Snap (OS), 2nd Heart Sound Split (A2_P2), and 3rd Heart Sound (S3), which is a crucial and at the same time difficult and complicated part of the heart sound diagnosis problem. The Multiple Decision Tree Architecture developed for the above diagnosis/differentiation problem has been tested with real heart sound signals, and its performance and generalisation capabilities were found to be higher than the previous ‘traditional’ architectures.
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Mathematics Subject Classification (2000):
68U35
D. Koutsouris: The authors would like to thank the clinician Dr D.E. Skarpalezos for his clinical support, Dr G. Koundourakis, and Neurosoft S.A. for their support and provision of Envisioner, a data-mining tool that was used to execute algorithms related to the Decision Trees.
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Stasis, A.C., Loukis, E.N., Pavlopoulos, S.A. et al. A multiple decision trees architecture for medical diagnosis: The differentiation of opening snap, second heart sound split and third heart sound. Computational Management Science 1, 245–274 (2004). https://doi.org/10.1007/s10287-004-0015-8
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DOI: https://doi.org/10.1007/s10287-004-0015-8