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Abstract Details

Mobilizing a Digital Research Ecosystem for Multiple Sclerosis Research and Care
Multiple Sclerosis
P3 - Poster Session 3 (5:30 PM-6:30 PM)
15-008

To improve our understanding of multiple sclerosis (MS) symptoms through remote data collection and design a platform that enables collaboration among all MS stakeholders (patient, clinician and researcher).

Every day, over three million people with MS face the dynamic consequences of unmeasured physiology, environmental conditions, and social determinants to their disease behavior.  Such diverse, volatile phenotypes isolate patients, complicate clinical care, and challenge the generalizability of scientific studies.  Recent advances in mobile computing (including wearable sensors) and machine learning enable novel research and clinical approaches to improve disease characterization and care.
MS Mosaic is a longitudinal study (current enrollment of 2000+ participants) and mobile research platform that combines community-based crowdsourcing and machine learning to systematically collect and analyze an unparalleled amount of data about the MS experience.  For improved symptom characterization, daily patient symptom and medication surveys are combined with bi-weekly MS functional composite (MSFC) activities and continuously collected wearable sensor data to facilitate symptom sub-typing and predict state changes.
Symptom subtypes are effectively discovered, and state changes accurately modelled, through novel machine learning methods.  Researchers, clinicians, patients, and software designers demonstrate effective collaboration on the initial development of a platform tailored to their collective and individual needs.
Collaboration among multiple stakeholders in the design and utilization of a chronic disease platform can generate unique insights into the disease experience that empowers patients, clinicians, and researchers.
Authors/Disclosures
Fletcher L. Hartsell III, MD, MPH (Duke Neurology)
PRESENTER
No disclosure on file
Katherine A. Heller, PhD No disclosure on file