Dr. Dr. Georg Spinner

Arbeit an der ZHAW

Tätigkeit

Dozent, Leitung Forschungsgruppe Medical Image Analysis & Data Modelling

Netzwerk

Mitglied in Netzwerken

• ZHAW Digital
• International Stroke Genetics Consortium
• ZHAW Datalab
• ZHAW Digital Health Lab

ORCID digital identifier

ORCID ID: 0000-0001-9640-8155

Projekte

• Delirium DynamiX / Projektleiter:in / laufend
• GEMINI: Mehrskalige digitale Zwillinge (Digital Twins) für Patient:innen mit ischämischem oder hämorrhagischem Schlaganfall / Teammitglied / laufend
• Digital Health Zurich: ein Praxislabor für patientenzentrierte klinische Innovation / Teammitglied / laufend
• IVIM: Muskelaktivierung in der Schulter / Projektleiter:in / abgeschlossen
• Stroke DynamiX – Graphische und kausale Netzwerke für das personalisierte Schlaganfallmanagement / Projektleiter:in / abgeschlossen
• Modellierung multizentrischer und dynamischer Schlaganfall Gesundheitsdaten / Projektleiter:in / abgeschlossen
• Datengetriebene Entscheidungsunterstützung bei intrakraniellen Aneurysmen und in der Spitalgastronomie mittels Bayes'schen Netzwerken / Projektleiter:in / abgeschlossen
• Evaluation von Methoden der Bayes'schen Modellierung für die Digitale Gesundheit / Projektleiter:in / abgeschlossen

Publikationen

Beiträge in wissenschaftlicher Zeitschrift, peer-reviewed

• Bührer, L. et al. (2026) 'Disentangling determinants of one-year modified Rankin Scale in patients with incidentally detected solitary intracranial aneurysms', Computers in Biology and Medicine, 210(111731). doi: 10.1016/j.compbiomed.2026.111731.
• Delucchi, M. et al. (2026) 'Mixed-effects additive Bayesian networks for the assessment of ruptured intracranial aneurysms : insights from multicenter data', Computers in Biology and Medicine, 201(111380). doi: 10.1016/j.compbiomed.2025.111380.
• Delucchi, M. et al. (2024) 'Additive Bayesian networks', Journal of Open Source Software, 9(101), p. 6822. doi: 10.21105/joss.06822.
• Marth, A. A. et al. (2024) 'Activation patterns of rotator-cuff muscles from quantitative IVIM DWI after physical testing', European Radiology Experimental, 8(96). doi: 10.1186/s41747-024-00487-5.
• Morel, S. et al. (2022) 'Intracranial aneurysm classifier using phenotypic factors : an international pooled analysis', Journal of Personalized Medicine, 12(9), p. 1410. doi: 10.3390/jpm12091410.
• Delucchi, M. et al. (2022) 'Bayesian network analysis reveals the interplay of intracranial aneurysm rupture risk factors', Computers in Biology and Medicine, 147(105740). doi: 10.1016/j.compbiomed.2022.105740.
• Spinner, G. R., Federau, C. and Kozerke, S. (2021) 'Bayesian inference using hierarchical and spatial priors for intravoxel incoherent motion MR imaging in the brain : analysis of cancer and acute stroke', Medical Image Analysis, 73(102144). doi: 10.1016/j.media.2021.102144.

Schriftliche Konferenzbeiträge, peer-reviewed

• Bührer, L. et al. (2026) 'Mapping the interplay of clinical risk factors in intracranial aneurysms using Additive Bayesian Networks', in European Causal Inference Meeting (euroCIM), Oxford, United Kingdom, 14-17 April 2026. ZHAW Zurich University of Applied Sciences. doi: 10.21256/zhaw-36581.
• Bijlenga, P. et al. (2025) 'Introducing Bayesian analysis for clinicians : sex-associated risk assessment of intracranial aneurysms', in Esposito, G. et al. (eds). Cham: Springer, pp. 19–26. doi: 10.1007/978-3-031-89844-0_3.
• Delucchi, M. et al. (2024) 'Insights from a multicenter Bayesian network study for advancing unruptured intracranial aneurysm management', in 8th International Conference on Computational and Mathematical Biomedical Engineering (CMBE), Arlington, VA, USA, 24-26 June 2024. Computational & Mathematical Biomedical Engineering.
• Delucchi, M. et al. (2023) 'An explainable multicentric analysis for understanding the aetiology of intracranial aneurysm disease', in Clinical and Translational Neuroscience. MDPI, pp. 46–47. doi: 10.3390/ctn7040039.
• Delucchi, M. et al. (2022) 'Bayesian networks to disentangle the interplay of intracranial aneurysm rupture risk factors', in Nithiarasu, P. and Vergara, C. (eds) CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering. Computational & Mathematical Biomedical Engineering, pp. 22–25.
• Spinner, G. R. et al. (2022) 'Survival analysis of intracranial aneurysm rupture to study the influence of clinical risk factors : towards a dynamic disease model', in Nithiarasu, P. and Vergara, C. (eds) CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering. Computational & Mathematical Biomedical Engineering, pp. 72–75.

Weitere Publikationen

• Bachmann, J. et al. (2025) Analysis of delirium in intensive care patients using Bayesian networks. medRxiv. doi: 10.1101/2025.09.23.25336328.
• Bührer, L. et al. (2025) 'Modelling the management of unruptured intracranial aneurysms', in 7th Digital Health Lab Day, Winterthur, Switzerland, 3 September 2025. ZHAW Zurich University of Applied Sciences. doi: 10.21256/zhaw-36580.
• Bührer, L. et al. (2024) 'Modelling the burden of disease of intracanial aneurysms', in 6th Digital Health Lab Day, Winterthur, Switzerland, 3 September 2024. ZHAW Zurich University of Applied Sciences. doi: 10.21256/zhaw-33654.
• Spinner, G. and Gerber, N. (2022) 'Datengetriebene Entscheidungsunterstützung mittels Bayes'scher Netzwerke', TRANSFER Spezial, p. 20. doi: 10.21256/zhaw-25930.
• Spinner, G. and Gerber, N. (2022) 'Bayesian network analysis for data-driven decision support', TRANSFER Special, p. 20. doi: 10.21256/zhaw-25931.
• Suter, S. et al. (2022) Visualization and analysis of wearable health data from COVID-19 patients. arXiv. doi: 10.21256/zhaw-24219.

Mündliche Konferenzbeiträge und Abstracts

Bührer, L. et al. (2025) 'Bayesian network analysis of SNPs rs11153071 and rs2107597 and clinical risk factors in intracranial aneurysms', in 32nd Workshop of the International Stroke Genomics Consortium, Gothenburg, Sweden, 14-16 May 2025.

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