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Making use of information from a cohort of 774 individuals, we show our deep-learning designs are able to distinguish between people with and without MS with a location underneath the receiver running characteristic bend of 0.88 (95% CI 0.70, 0.88). Our experimental results suggest that digital biomarkers produced from smartphone data could as time goes on be used as extra diagnostic criteria for MS.Person reidentification (reID) by convolutional neural network (CNN)-based comm
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