Prof. Dr. Sven Hirsch

Prof. Dr. Sven Hirsch

ZHAW Life Sciences und Facility Management
Institut für Computational Life Sciences
Schloss
8820 Wädenswil

+41 (0) 58 934 54 44
sven.hirsch@zhaw.ch

Arbeit an der ZHAW

Tätigkeit

Arbeits- und Forschungsschwerpunkte

Künstliche Intelligenz in der Medizin, Digital Patient Twin, Biomedizinische Simulation und Modellierung, Digital Health
Medizinische Bildanalyse & Diagnostik Systeme, Modellierung biomedizinischer Prozesse, Datenintegration, maschinelles Lernen, Sensor- und Zeitreihenanalyse
Ästhetik der Digitalisierung und ihre Implikation für die Gesellschaft, Wissenschaftlicher Kurator der Stiftung Insel Hombroich

Lehrtätigkeit

Berufserfahrung

Promotionsrecht UZH
Universität Zürich
12 / 2023 - heute
Leiter Center for Computational Health
ZHAW, Institute of Computational Life Sciences
01 / 2022 - heute
Leiter Biomedizinsche Simulation
ZHAW, Institut für angewandte Simulation
09 / 2013 - 12 / 2021
Künstler (a.k.a Sven Mann) in Medien- und Klangkunst
freischaffend
01 / 2000 - 09 / 2019
Senior Foresight Consultant, Leiter Quantifizierung
Z_punkt, The foresight company
05 / 2008 - 06 / 2017
Leiter Biomedical Simulation
ETH Zürich, Institut für Bildwissenschaften (Prof. Székely)
07 / 2008 - 08 / 2013
Projektleiter Holographische Vermessung
ViRad Imaging/Uniklinik Düsseldorf/caesar Bonn
02 / 2007 - 08 / 2008
Wissenschaftl. Assistent Holographische Gesichtsvermessung
Kantonspital Basel
10 / 2003 - 01 / 2007

Aus- und Weiterbildung

Ausbildung

Promotion / Laser Physik
Universität Düsseldorf
09 / 2003 - 01 / 2007
Postgradualer Master / Audiovisuelle Medien
Kunsthochschule für Medien, Köln
09 / 1999 - 09 / 2002
Diplom Physiker, Digitale Bildverarbeitung und Physiologie / Physik
Universität Heidelberg
09 / 1993 - 07 / 1998
Vordiplom / Physik
Universität Mainz
10 / 1991 - 08 / 1993

Weiterbildung

CAS Leadership & Governance for Higher Education
Universität Zürich
07 / 2023
Professor ZFH
ZHAW
06 / 2016
CAS Hochschuldidaktik
PH Zürich
07 / 2015
PhD Laserphysik
Heinrich Heine Universität Düsseldorf
01 / 2007

Netzwerk

Mitglied in Netzwerken

ORCID digital identifier

ORCID ID: 0000-0002-5678-4110

Auszeichnungen

prix sante neXt 23
sante neXt
05 / 2023

Social Media

Medienpräsenz

Prix SaneneXt

Projekte

Publikationen

Beiträge in wissenschaftlicher Zeitschrift, peer-reviewed

Gram, J. S. et al. (2026) 'Evaluating a telemedical follow-up program for continuity of care after hospital discharge : prospective clinical intervention study', JMIR Formative Research, 2026(10), p. e85467. doi: 10.2196/85467.
Amacker, J. et al. (2026) 'Shared local brain dynamics in pediatric and adult NREM parasomnias', Sleep. doi: 10.1093/sleep/zsag123.
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.
Musio, F. et al. (2026) 'Circle of Willis centerline graphs : a dataset and baseline algorithm', Neuroscience Informatics, 6(1), p. 100265. doi: 10.1016/j.neuri.2026.100265.
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.
Difrancesco, S. et al. (2025) 'Collaborative design and development of a patient-centered digital health app for supportive cancer care : participatory study', JMIR Human Factors, 12(e73829). doi: 10.2196/73829.
Kirchberger, J. et al. (2025) 'An explorative study on movement detection using wearable sensors in acute care hospital patients', Scientific Reports, 15(1), p. 19941. doi: 10.1038/s41598-025-04340-6.
Reichl, J. J. et al. (2024) 'Pilot study for the development of an automatically generated and wearable-based early warning system for the detection of deterioration of hospitalized patients of an acute care hospital', Archives of Public Health, 82(1), p. 179. doi: 10.1186/s13690-024-01409-y.
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.
Mack, I. et al. (2022) 'Wearable technologies for pediatric patients with surgical infections : more than counting steps?', Biosensors, 12(8), p. 634. doi: 10.3390/bios12080634.
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.
Juchler, N. et al. (2022) 'Shape trumps size : image-based morphological analysis reveals that the 3D shape discriminates intracranial aneurysm disease status better than aneurysm size', Frontiers in Neurology, 13(809391). doi: 10.3389/fneur.2022.809391.
Eibl, D. et al. (2021) 'Keeping SARS-CoV-2 out : vaccines, filters, and self-disinfecting textiles', Chimia, 75(3), pp. 215–218. doi: 10.2533/chimia.2021.215.
Morel, S. et al. (2021) 'Effects of low and high aneurysmal wall shear stress on endothelial cell behavior : differences and similarities', Frontiers in Physiology, 12(727338). doi: 10.3389/fphys.2021.727338.
Borčinová, M. et al. (2020) 'Production and secretion dynamics of prokaryotic Penicillin G acylase in Pichia pastoris', Applied Microbiology and Biotechnology, 104(13), pp. 5787–5800. doi: 10.1007/s00253-020-10669-x.
Bakker, M. K. et al. (2020) 'Genome-wide association study of intracranial aneurysms identifies 17 risk loci and genetic overlap with clinical risk factors', Nature Genetics, 52(12), pp. 1303–1313. doi: 10.1038/s41588-020-00725-7.
Juchler, N. et al. (2020) 'Shape irregularity of the intracranial aneurysm lumen exhibits diagnostic value', Acta Neurochirurgica, 162(9), pp. 2261–2270. doi: 10.1007/s00701-020-04428-0.
Juchler, N. et al. (2020) 'Radiomics approach to quantify shape irregularity from crowd-based qualitative assessment of intracranial aneurysms', Computer Methods in Biomechanics and Biomedical Engineering : Imaging & Visualization, 8(5), pp. 538–546. doi: 10.1080/21681163.2020.1728579.
Detmer, F. J. et al. (2020) 'Incorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessment', Acta Neurochirurgica, 162(3), pp. 553–566. doi: 10.1007/s00701-020-04234-8.
Detmer, F. J. et al. (2020) 'Comparison of statistical learning approaches for cerebral aneurysm rupture assessment', International Journal of Computer Assisted Radiology and Surgery, 15(1), pp. 141–150. doi: 10.1007/s11548-019-02065-2.
Detmer, F. J. et al. (2019) 'Extending statistical learning for aneurysm rupture assessment to Finnish and Japanese populations using morphology, hemodynamics, and patient characteristics', Neurosurgical Focus, 47(1). doi: 10.3171/2019.4.FOCUS19145.
Detmer, F. J. et al. (2018) 'External validation of cerebral aneurysm rupture probability model with data from two patient cohorts', Acta Neurochirurgica. doi: 10.1007/s00701-018-3712-8.
Bijlenga, P. et al. (2017) 'PHASES score for the management of intracranial aneurysm', Stroke: A Journal of Cerebral Circulation, 48(8), pp. 2105–2112. doi: 10.1161/STROKEAHA.117.017391.
Daheim, C. and Hirsch, S. (2015) 'Emerging practices in foresight and their use in STI policy', STI Policy Review, 6(2), pp. 24–53.
Schneider, M. et al. (2015) 'Joint 3-D vessel segmentation and centerline extraction using oblique Hough forests with steerable filters', Medical Image Analysis, 19(1), pp. 220–249. doi: 10.1016/j.media.2014.09.007.
Gessat, M. et al. (2014) 'Image-based mechanical analysis of stent deformation : concept and exemplary implementation for aortic valve stents', IEEE Transactions on Biomedical Engineering, 61(1), pp. 4–15. doi: 10.1109/TBME.2013.2273496.
Hirsch, S., Burggraf, P. and Daheim, C. (2013) 'Scenario planning with integrated quantification : managing uncertainty in corporate strategy building', Foresight, 15(5), pp. 363–374. doi: 10.1108/FS-09-2012-0064.

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.
Musio, F. et al. (2024) 'Quantitative evaluation of the Circle of Willis vascular architecture in 3D CT and MR angiography', in Nithiarasu, P. and Lohner, R. (eds) CMBE24: 8th International Conference on Computational & Mathematical Biomedical Engineering. Computational & Mathematical Biomedical Engineering, pp. 563–566. doi: 10.21256/zhaw-31451.
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.
Dupuy, N. et al. (2022) 'Exploring intracranial aneurysm instability markers to improve disease modeling', in Nithiarasu, P. and Vergara, C. (eds) CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering. Computational & Mathematical Biomedical Engineering, pp. 14–17. doi: 10.21256/zhaw-25387.
Juchler, N., Bijlenga, P. and Hirsch, S. (2022) 'Modeling the location-dependency of aneurysm shape : a morphometric comparative study', in Nithiarasu, P. and Vergara, C. (eds) CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering. Computational & Mathematical Biomedical Engineering, pp. 703–705. doi: 10.21256/zhaw-25388.
Juchler, N., Bijlenga, P. and Hirsch, S. (2022) 'The role of shape for aneurysm risk assessment', in Nithiarasu, P. and Vergara, C. (eds) CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering. Computational & Mathematical Biomedical Engineering, pp. 84–86. doi: 10.21256/zhaw-25386.
Watanabe, K. et al. (2020) 'Influence of input image configurations on output of a convolutional neural network to detect cerebral aneurysms', in International Mechanical Engineering Congress and Exposition : Volume 3 - biomedical and biotechnology engineering. The American Society of Mechanical Engineers. doi: 10.1115/IMECE2019-11125.
Juchler, N. et al. (2019) 'Understanding morphological irregularity : a rater-based study', in CMBE19 Proceedings. Cardiff: Zeta Computational Resources, p. 583.
Juchler, N. et al. (2019) 'Identification of clinically relevant characteristics of intracranial aneurysm morphology', in 1. Digital Health Lab Day (Life in Numbers 5), Wädenswil, 3. October 2019. ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
Schilling, S. et al. (2017) 'Endothelial cell elongation under shear stress : a computational model to consolidate observed cell shape changes', in Nithiarasu, P. and Robertson, A. M. (eds) 5th International Conference on Computational and Mathematical Biomedical Engineering, CMBE2017. Swansea: Zeta Computational Resources, pp. 850–852.
Juchler, N. et al. (2017) 'Measuring the perceived morphological complexity of intracranial aneurysms', in Abstract Book, 3rd International SystemsX.ch Conference on Systems Biology, p. 160. doi: 10.3929/ethz-b-000176201.
Juchler, N. et al. (2016) 'Shape-based assessment of intracranial aneurysm disease status – a machine learning approach', in All SystemsX.ch Day, Bern, 1 September 2016.
Juchler, N. et al. (2016) 'What's ugly? : shape-based analysis of intracranial aneurysms', in Latsis Symposium 2016 : Personalized Medicine, Zurich, 27-29 June 2016.
Koltukluoglu, T. S. et al. (2015) 'A robust comparison approach of velocity data between MRI and CFD based on divergence-free space projection', in 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI). IEEE, pp. 1393–1397. doi: 10.1109/ISBI.2015.7164136.
Koltukluoglu, T. S. et al. (2015) 'A partial domain approach to enable aortic flow simulation without turbulent modeling', in Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 Part II. Springer, pp. 544–551. doi: 10.1007/978-3-319-24571-3_65.
Juchler, N. et al. (2015) 'On the utility of 3D Zernike Moment Invariants to assess aneurysm disease status', in All SystemsX.ch Day, Bern, 15 September 2015.
Russ, C. et al. (2014) 'Computational stent placement in transcatheter aortic valve implantation', in Biomedical Simulation. Cham: Springer, pp. 95–105. doi: 10.1007/978-3-319-12057-7_11.
Schneider, M. et al. (2014) 'TGIF : topological gap in-fill for vascular networks', in Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 Part II. Cham: Springer, pp. 89–96. doi: 10.1007/978-3-319-10470-6_12.
Russ, C. et al. (2013) 'Simulation of transcatheter aortic valve implantation under consideration of leaflet calcification', in 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, pp. 711–714. doi: 10.1109/EMBC.2013.6609599.
Hirsch, S. et al. (2013) 'Clinical relevance of mechano-biological transduction in intracranial aneurysms : the mediating role of thrombus formation and inflammatory response expressing as aneurysm shape', in CMBE13 : 3rd International Conference on Computational & Mathematical Biomedical Engineering. Hong Kong: City University of Hong Kong, pp. 107–110.

Weitere Publikationen

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.
Gerber, N. et al. (2022) 'Zusammenarbeit und wissenschaftlicher Austausch sind der Schlüssel zu erfolgreicher Forschung : der ZHAW Health Research Hub bringt's unter einen Hut', Clinicum, 2022(6), pp. 80–81. doi: 10.21256/zhaw-26376.
Suter, S. et al. (2022) Visualization and analysis of wearable health data from COVID-19 patients. arXiv. doi: 10.21256/zhaw-24219.
Bakker, M. K. et al. (2021) 'Author Correction: Genome-wide association study of intracranial aneurysms identifies 17 risk loci and genetic overlap with clinical risk factors', Nature Genetics, 53(2), p. 254. doi: 10.1038/s41588-020-00760-4.
Bijlenga, P. et al. (2019) 'Plea for an international Aneurysm Data Bank : description and perspectives', Neurosurgical Focus, 47(1), p. E17. doi: 10.3171/2019.4.FOCUS19185.
Juchler, N. et al. (2016) 'Shape-based assessment of intracranial aneurysm disease status', in ZNZ Symposium 2016, Zurich, 15. September 2016.

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.
Musio, F. et al. (2023) 'Circle of Willis configurations in stroke patients', in 19th Interdisciplinary Cerebrovascular Symposium, Geneva, Switzerland, 17-19 August 2023.
Melloh, M. and Hirsch, S. (2019) 'How universities can lead the transformation to digital health', in Digital Health Conclave, Bangalore, India, 8 April 2019.
Hirsch, S. and Juchler, N. (2019) 'Real and assumed insights : statistical models and imaging biomarkers for disease characterization of intracranial aneurysms', in 1. Digital Health Lab Day (Life in Numbers 5), Wädenswil, 3. October 2019.
Watanabe, K. et al. (2018) 'Effect of input image representation for results of neural network to detect cerebral aneurysms', in 31st Bioengineering Conference / 2018 Annual Meeting of BED/JSME, Koriyama, Japan, 14-15 December 2018.
Juchler, N. et al. (2018) 'Clinical data sharing : a data scientist's perspective', in Life in Numbers 4, Wädenswil, 4 October 2018.
Juchler, N. et al. (2018) 'Reproducing qualitative irregularity ratings by means of quantitative shape descriptors in intracranial aneurysms', in 8th World Congress of Biomechanics (WCB2018), Dublin, Ireland, 8-12 July 2018.
Juchler, N. et al. (2018) 'Aneurysm shape as a diagnostic tool', in Kick-Off Event: PhD Network in Data Science, Winterthur, 13. April 2018.
Anzai, H. et al. (2018) 'Correlation of CFD with wall enhancement', in iNEW, Zürich, 8. Februar 2018.
Juchler, N. et al. (2018) 'Aneurysm shape as a diagnostic tool : a machine learning approach', in International Neurovascular Exploratory Workshop (iNEW′2018), Zürich, 7-9 February 2018.
Hirsch, S. et al. (2018) 'Using machine learning to identify shape biomarkers in intracranial aneurysm', in Life Science Zurich Impact, Zürich, 22 January 2018.
Hirsch, S. et al. (2017) 'Big Data : machine learning to identify shape biomarkers in intracranial aneurysm', in Annual Meeting of the Swiss Society for Biomedical Engineering (SSBE), Winterthur, 30 August 2017.
Anzai, H. et al. (2017) 'Where does CFD identify lesion instability in small aneurysms?', in CMBE17 : 5th International Conference on Computational and Mathematical Biomedical Engineering.
Juchler, N. et al. (2017) 'Using shape descriptors to categorize intracranial aneurysms', in CMBE17 : 5th International Conference on Computational and Mathematical Biomedical Engineering.
Juchler, N. et al. (2016) 'Shape-based modeling of aneurysmal disease status', in ECCOMAS Congress 2016, Heraklion, Greece, 5-10 June 2016.
Bijlenga, P. and Hirsch, S. (2015) 'Intracranial aneurysms rupture risk clinical assessment', in 9th European Solid Mechanics Conference (ESMC), Madrid, Spain, 6-10 July 2015.
Egger, J. et al. (2015) 'The role of clot maturation inside intracranial aneurysms using a viscoelastic thrombosis model', in 9th European Solid Mechanics Conference (ESMC), Madrid, Spain, 6-10 July 2015.
Neufeld, E. et al. (2015) 'Computational framework for personalized characterization of aneurysm physics and physiology, as well as disease progression modelling', in 9th European Solid Mechanics Conference (ESMC), Madrid, Spain, 6-10 July 2015.
Egger, J. et al. (2014) '2D viscoelastic thrombosis model for stented aneurysms', in 7th World Congress of Biomechanics, Boston, USA, 06-11 July 2014.

Forschungsdaten

Juchler, Norman; Bijlenga, Philippe; Hirsch, Sven, 2022. AneuX morphology database. Zenodo. Verfügbar unter: https://doi.org/10.5281/zenodo.6678442

Interessenbindungen

Aktuelle Interessenbindungen

Stiftung Insel Hombroich: Mitglied des Kuratoriums
In der Stiftung Insel Hombroich, Neuss, bin ich Kuratoriumsmitglied im Bereich Wissenschaft. Die Stiftung beschäftigt sich mit der Verwaltung und Weiterentwicklung der Insel Hombroich. Hombroich ist das dynamische und vielfältige Zusammenspiel von Kunst, Natur, Bauwerken, Sammlungen, Archiven und Menschen. Der Ort Hombroich verbindet Künstlerinnen und Künstler, Wissenschaftlerinnen und Wissenschaftler, Stiftungsmitarbeitende, Ehrenamtliche und assoziierte Institutionen., Neuss
09 / 2018 - 12 / 2030

Zurück