Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0010-4825(02)00006-9
Title: Combining neural network predictions for medical diagnosis
Authors: Hayashi, Y.
Setiono, R. 
Keywords: Feedforward neural network
Hepatobiliary disorder
Medical diagnosis
Neural network ensemble
Simple averaging
Issue Date: 2002
Source: Hayashi, Y., Setiono, R. (2002). Combining neural network predictions for medical diagnosis. Computers in Biology and Medicine 32 (4) : 237-246. ScholarBank@NUS Repository. https://doi.org/10.1016/S0010-4825(02)00006-9
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. © 2002 Elsevier Science Ltd. All rights reserved.
Source Title: Computers in Biology and Medicine
URI: http://scholarbank.nus.edu.sg/handle/10635/42403
ISSN: 00104825
DOI: 10.1016/S0010-4825(02)00006-9
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