Novel time series analysis approach for prediction of dialysis in critically ill patients using echo-state networks
Thierry Verplancke, Stijn Van Looy, Kristof Steurbaut, Dominique Benoît, Filip De Turck, Georges De Moor, Johan M. A. Decruyenaere · Critical Care · 2009
Echo-state networks are part of a group of reservoir computing methods and are basically a form of recurrent artificial neural networks. These methods can perform classification tasks on time-series data. The recurrent artificial neural network of an echo-state network has an echo-state characteristic. This echo state functions as a fading memory: samples that have been introduced into the network in a further past are faded away. The echo-state approach for the training of recurrent neural networks was first described by Jaeger [ 1 ]. In clinical medicine, until this moment, no original research articles have been published to examine the use of echo-state networks.