This study will make use of a cross-sectional design of MG patients and non-MG participants to quantitatively assess key MG symptoms, and to explore the applicability of machine learning algorithms to their measurement.
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Differentiating between MG-patients and non-MG participants using digital features of dysarhtria, dysphonia, proximal arm fatigue and ptosis.
Timeframe: Assessed at a single time point during outpatient visit