Combining neural network predictions for medical diagnosis

Computers in Biology and Medicine
Yoichi Hayashi, R Setiono

Abstract

We present our results from combining the predictions of an ensemble of neural networks for the diagnosis of hepatobiliary disorders. To improve the accuracy of the diagnosis, we train the second level networks using the outputs of the first level networks as input data. The second level networks achieve an accuracy that is higher than that of the individual networks in the first level. Compared to the simple method which averages the outputs of the first level networks, the second level networks are also more accurate. We discuss how the overall predictive accuracy can be improved by introducing bias during the training of the level one networks.

References

Jan 1, 1992·IEEE Transactions on Neural Networks·S K Pal, S Mitra

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Citations

Jan 20, 2007·Journal of Medical Systems·Elif Derya Ubeyli
Jun 1, 2005·Computer Methods and Programs in Biomedicine·Fatimah IbrahimSaadiah Sulaiman
May 23, 2012·IEEE Transactions on Information Technology in Biomedicine : a Publication of the IEEE Engineering in Medicine and Biology Society·Ching-Seh WuHemant Shah
Aug 5, 2015·IEEE Journal of Biomedical and Health Informatics·Andreas C NeocleousChristos N Schizas

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