Georg Spinner, PhD, MD

Work at ZHAW

Position

Lecturer, Head research group Medical Image Analysis & Data Modelling

Network

ORCID digital identifier

ORCID ID: 0000-0001-9640-8155

Projects

• Delirium DynamiX / Project leader / ongoing
• GEMINI: A Generation of Multi-scale Digital Twins of Ischaemic and Haemorrhagic Stroke Patients / Team member / ongoing
• Digital Health Zurich: a practice lab for patient-centred clinical innovation / Team member / ongoing
• IVIM: muscle activation of the shoulder / Project leader / completed
• Stroke DynamiX – Graphical and Causal Networks for Personalized Stroke Management / Project leader / completed
• Modeling of multicentric and dynamic stroke health data / Project leader / completed
• Data-driven decision support for intracranial aneurysms and hospital catering using Bayesian networks / Project leader / completed

Publications

Articles in scientific journal, 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.

Written conference contributions, 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.

Other publications

• 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.

Oral conference contributions and 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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