DEANN : A healthcare analytic methodology of data envelopment analysis and arti fi cial neural networks for the prediction of organ recipient functional status

@inproceedings{Misiunas2015DEANNA,
  title={DEANN : A healthcare analytic methodology of data envelopment analysis and arti fi cial neural networks for the prediction of organ recipient functional status},
  author={Nicholas Misiunas and Asil Oztekin and Yao Chen and Kavitha Chandra},
  year={2015}
}
The problem of effectively preprocessing a dataset containing a large number of performance metrics and an even larger number of records is crucial when utilizing an ANN. As such, this study proposes deploying DEA to preprocess the data to remove outliers and hence, preserve monotonicity as well as to reduce the size of the dataset used to train the ANN. The results of this novel data analytic approach, i.e. DEANN, proved that the accuracy of the ANN can be maintained while the size of the… CONTINUE READING
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