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Fig. 4 | BMC Neurology

Fig. 4

From: Machine learning analysis of motor evoked potential time series to predict disability progression in multiple sclerosis

Fig. 4

Results of the disability progression task Results are shown for different sizes of training set. Each point represents an average over 100 000 test sets, with the error bar indicating the standard deviation. Results are shown for the baseline model which uses a subset of known features (Latency, EDSS at T0 and age), as well as a model where we add additional TS features. Abbreviations used: RF Random Forest, LR Logistic Regression, TS Time series. These results are represented numerically in Table 2

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