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DeMMO: Longitudinal and Cross-Disease Modelling of Digital Mobility Outcomes via Multi-Task Learning
Digital mobility outcomes (DMOs) derived from wearable sensors characterise mobility in daily life and offer a promising means of monitoring disease progression. However, existing DMO studies have typically focused on either a single disease or a single visit. To the best of our knowledge, we are the first to define and study the practical problem of cross-disease longitudinal DMO modelling. We argue that this problem should satisfy at least two requirements. First, the temporal progression of DMOs should be modelled within each disease, as mobility-limiting diseases evolve over time. Second,
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-25T19:07:32.000Z
First collected: 2026-09-21T09:42:05.193Z. This is not the publication date.