A Hybrid Approach for MS Diagnosis Through Nonlinear EEG Descriptors and Metaheuristic Optimized Classification Learning

<div>The proposed model in the diagnosis of MS disease is applied to two unseen data sets with 4000 signals (i.e., 2000 healthy and 2000 with MS disease). The results of applying the method are displayed in three random folds.</div>

Computational Intelligence and Neuroscience

fig6

Figure 6

Figure 6: A Hybrid Approach for MS Diagnosis Through Nonlinear EEG Descriptors and Metaheuristic Optimized Classification Learning 