Citizen-controlled Data Science for Multiple Sclerosis Research

Co-PIs:

  • Ernst Hafen (ETH Zürich),
  • Gunnar Rätsch (ETH Zürich),
  • Murat Sariyar (BFH)
  • Andreas Lutterotti (USZ)
  • Serge Bignens (ETH Zürich)
  • Bernd Rinn (ETH Zürich)

Problem:

Personalized medicine relies on the longitudinal collection, integration and analysis of different health related data for individualized prevention and treatment of disease. Required data include clinical and environmental data and increasingly data collected continuously by the individual using smartphone Apps or wearable sensors (mHealth)

Solution:

  1. A secure and trusted citizen-controlled data science infrastructure for the integration, analysis and visualization of mobile health, medical and environmental data
  2. And a case study on the basis of fatigue in Multiple Sclerosis patients

Impact:

  1. Clinical researchers have access to a secure, federated data infrastructure, on which algorithms can access open environmental data and personal health data with the consent of study participant.
  2. New findings in the domain of multiple sclerosis.