Stroke DynamiX
Graphical and Causal Networks for Personalized Stroke Management
Description
Stroke DynamiX explores data-driven stroke management using machine-learning techniques in a consortium of statistics researchers, translational enablers, and clinical partners. We implement statistical tools to dynamically model stroke epidemiologically and predict real-time sepsis onset in the clinic.
Key Data
Projectlead
Deputy Projectlead
Co-Projectlead
Prof. Dr. Reinhard Furrer, Dr. Zsolt Kulcsar
Project team
Project partners
Universitätsspital Zürich; Hôpitaux universitaires de Genève
Project status
ongoing, started 05/2023
Funding partner
Kanton Zürich / Digitalisierungsinitiative DIZH
Project budget
599'866 CHF
