Accurate prediction of clinical stroke scales and improved biomarkers of motor impairment from robotic measurements
Fig 2
Schematic illustration of the ensemble neural network models used to predict the clinical scales from the RMK variables.
Each subset of features identified by the artificial ant algorithm was used to construct 10 independent neural network models using exactly the same network topology and training parameters but a different random seed number (and thus different initial synaptic parameters and presentation sequence of the training samples). The predictions of these 10 models were averaged to produce the aggregate prediction of the ensemble.