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We use the Bayesian Model Averaging (BMA) over Decision Trees (DTs) for assessing newborn brain maturity from clinical EEG. We found that within this methodology an appreciable part of EEG features is rarely used in the DT models, because these features make weak contribution to the assessment. It was identified that the portion of DT models using weak EEG features is large. The negative impact of...
A new learning algorithm for Evolving Cascade Neural Networks (ECNNs) is described. An ECNN starts to learn with one input node and then adding new inputs as well as new hidden neurons evolves it. The trained ECNN has a nearly minimal number of input and hidden neurons as well as connections. The algorithm was successfully applied to classify artifacts and normal segments in clinical electroencephalograms...
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