Boosted Networks for the Diagnosis of Cardiovascular Diseases
DOI:
https://doi.org/10.21533/pen.v1.i2.1843Abstract
A boosting by filtering technique for neural network systems with back propagation together with a majority
voting scheme is presented in this paper. Previous research with regards to predict the presence of
cardiovascular diseases has shown accuracy rates up to 72.9%. Using a boosting by filtering technique
prediction accuracy increased over 80%. The designed neural network system in this article presents a significant
increase of robustness and it is shown that by majority voting of the parallel networks, recognition rates reach to
> 90 in the V.A. Medical Center, Long Beach and Cleveland Clinic Foundation data set.
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