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 (Universität Zürich), Dr. Zsolt Kulcsar (Universitätsspital Zürich)
Project team
Dr. Jan Bartussek (Universitätsspital Zürich), Matteo Delucchi, Dr. Norman Juchler
Project partners
Universität Zürich; Universitätsspital Zürich; Hôpitaux universitaires de Genève
Project status
ongoing, started 05/2023
Institute/Centre
Institute of Computational Life Sciences (ICLS)
Funding partner
Digitalisierungsinitiative der Zürcher Hochschulen DIZH
Project budget
599'866 CHF
Further documents and links
Publications
-
Additive Bayesian networks
2024 Delucchi, Matteo; Liechti, Jonas I.; Spinner, Georg; Furrer, Reinhard
-
An explainable multicentric analysis for understanding the aetiology of intracranial aneurysm disease
2023 Delucchi, Matteo; Spinner, Georg R.; Bijlenga, Philippe; Morel, Sandrine; Hostettler, Isabel; Werring, David; Wostrack, Maria; Meyer, Bernhard; Bourcier, Romain; Lindgren, Antti; Bakker, Mark K.; Ruigrok, Ynte M.; Furrer, Reinhard; Hirsch, Sven
