Multiple Organ Failure Diagnosis Using Adverse Events and Neural Networks [chapter]

Álvaro Silva, Paulo Cortez, Manuel Santos, Lopes Gomes, José Neves
<i title="Springer-Verlag"> <a target="_blank" rel="noopener" href="" style="color: black;">Enterprise Information Systems VI</a> </i> &nbsp;
In the past years, the Clinical Data Mining arena has suffered a remarkable development, where intelligent data analysis tools, such as Neural Networks, have been successfully applied in the design of medical systems. In this work, Neural Networks are applied to the prediction of organ dysfunction in Intensive Care Units. The novelty of this approach comes from the use of adverse events, which are triggered from four bedside alarms, being achieved an overall predictive accuracy of 70%.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1007/1-4020-3675-2_15</a> <a target="_blank" rel="external noopener" href="">dblp:conf/iceis/Silva0SG004</a> <a target="_blank" rel="external noopener" href="">fatcat:qcig7umlv5eqdnjz3l3h52eaiy</a> </span>
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