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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

Prof. Dr. Sven Hirsch

Co-Projectlead

Prof. Dr. Reinhard Furrer, Dr. Zsolt Kulcsar

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