Modeling of multicentric and dynamic stroke health data
Result
Peer-reviewed journal publication incl. software (R package): Delucchi et al., (2024). Additive Bayesian Networks. Journal of Open Source Software, 9(101), 6822, https://doi.org/10.21105/joss.06822
Additional preparation work for follow-up projects
Description
The aim of the project is the further development of probabilistic and dynamic modeling of diseases in the form of Bayesian networks in the field of digital health as a central strategic pillar of the newly formed specialist group "Medical Image Analysis and Data Modeling" of the "Computational Health" focus. To this end, two pathologies of stroke are examined using multicentric data: ruptured intracranial aneurysms and ischemic stroke.
Key data
Projectlead
Project team
Matteo Delucchi, Prof. Dr. Philippe Bijlenga (Hôpitaux universitaires de Genève), Prof. Dr. Reinhard Furrer (Universität Zürich UZH), Dr. Zsolt Kulcsar (Universitätsspital Zürich USZ)
Project partners
Hôpitaux universitaires de Genève; Universität Zürich UZH; Universitätsspital Zürich USZ; International Stroke Genetics Consortium (ISGC)
Project status
completed, 01/2023 - 12/2024
Institute/Centre
Institute of Computational Life Sciences (ICLS)
Funding partner
Internal
Project budget
25'000 CHF
Publications
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Insights from a multicenter Bayesian network study for advancing unruptured intracranial aneurysm management
2024 Delucchi, Matteo; Spinner, Georg; Furrer, Reinhard; Bijlenga, Philippe; Hirsch, Sven
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Additive Bayesian networks
2024 Delucchi, Matteo; Liechti, Jonas I.; Spinner, Georg; Furrer, Reinhard
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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
School of Life Sciences and Facility Management
Schloss
8820 Wädenswil