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
Prof. Dr. Philippe Bijlenga (Hôpitaux universitaires de Genève ), Matteo Delucchi, Prof. Dr. Reinhard Furrer (Universität Zürich ), Dr. Zsolt Kulcsar (Universitätsspital Zürich )
Project partners
Hôpitaux universitaires de Genève; Universität Zürich; Universitätsspital Zürich; International Stroke Genetics Consortium (ISGC)
Project status
ongoing, started 01/2023
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
