REal-time data monitoring for Shared, Adaptive, Multi-domain and Personalised prediction and decision making for Long-term Pulmonary care Ecosystems

  • Duration:

Multi-morbid complex chronic conditions (CCCs) are highly prevalent in patients with Chronic Obstructive Pulmonary Disease (COPD) and timely and preventive care is essential. RE-SAMPLE will improve CCC disease management by creating a knowledge base of multimodal data from health records, clinical studies, expert and patient knowledge and guidelines, and extend this with state-of-the-art Real World Data collection. Predictive modelling through privacy-preserving Artificial Intelligence (AI), will increase the understanding of CCCs including the interdependence of multi-morbidities, and evidence in effective interventions for CCC disease management. As such RE-SAMPLE will act upon the need for diversified, personalized care to alleviate the overall societal and economic burden of these CCCs.


University of Twente, Netherlands Medisch Spectrum Twente hospital, Netherlands University of Piraeus Systems Security Lab, Greece Tartu Ülikooli Kliinikum, Estonia Policlinico Gemelli hospital, Italy European Hospital and Healthcare Federation, Belgium Atos IT Solutions and Services, Spain Roessingh Research and Development, Netherlands Innovation Sprint, Belgium

Share project:

Contact Person
Dr.-Ing. Serge Autexier

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz