Prof. Sven Hirsch, PhD

ZHAW School of Life Sciences and Facility Management
Institute of Computational Life Sciences
Schloss
8820 Wädenswil

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

Work at ZHAW

Position

Focus

Artificial Intelligence (AI) in Medicine, Digital Patient Twin, Biomedical Modeling and Simulation, Digital Health
Medical imaging analysis & diagnostics systems, Modelling of biomedical processes, Data assimilation and machine intelligence, Sensor and time series analysis
Aesthetics of digitalisation and its implications on society, Chair for Sciences in the Board of Foundation Insel Hombroich

Teaching

Experience

Right to confer PhD UZH
University Zurich
12 / 2023 - today
Head of Center for Computational Health
ZHAW, Institute of Computational Life Sciences
01 / 2022 - today
Group Head Biomedical Simulation
ZHAW, Institute of Applied Simulation
09 / 2013 - 12 / 2021
Media artist
self-employed
01 / 2000 - 09 / 2019
Senior Foresight Consultant, Head of Quantification
Z_punkt, The foresight company
05 / 2008 - 06 / 2017
Group Leader Biomedical Simulation
ETH Zurich, Computer vision lab (Prof. Székely)
07 / 2008 - 08 / 2013
Project lead holographic topometry
ViRad Imaging/Uniklinik Düsseldorf/caesar Bonn
02 / 2007 - 08 / 2008
Assistent holographic facial topometry
Kantonspital Basel
10 / 2003 - 01 / 2007

Education and Continuing education

Education

PhD / Laser Physics
University Düsseldorf
09 / 2003 - 01 / 2007
Postgrad. Master / Audiovisual Media
Acedemy for Media Arts, Cologne
09 / 1999 - 09 / 2002
Physicist, Digital Image Processing and Physiology / Physics
University Heidelberg
09 / 1993 - 07 / 1998
Vordiplom / Physics
University Mainz
10 / 1991 - 08 / 1993

Continuing Education

CAS Leadership & Governance for Higher Education
University of Zurich
07 / 2023
Professor
ZHAW
06 / 2016
CAS didactics for higher education
PH Zurich
07 / 2015
PhD Laser Physics
Heinrich Heine University Düsseldorf
01 / 2007

Network

ORCID digital identifier

ORCID ID: 0000-0002-5678-4110

Social media

Projects

Publications

Articles in scientific journal, peer-reviewed

Gram, J. S., Meier, R., Hölz, B., Abdelhamid, K., Lang, T., Imfeld, L., Rotte, H., Warthmann, I., Zweipfenning, S., Casper, K., Häner, R., Schödler, A. L., Thai, W., Abel, C., Aeschlimann, N., Ingrisani, M., Ledergerber, I., Sommer-Meyer, C., Mayer, V. G. A., 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), e85467. https://doi.org/10.2196/85467
Musio, F., Juchler, N., Yang, K., Shit, S., Prabhakar, C., Menze, B., & Hirsch, S. (2026). Circle of Willis centerline graphs : a dataset and baseline algorithm. Neuroscience Informatics, 6(1), 100265. https://doi.org/10.1016/j.neuri.2026.100265
Delucchi, M., Bijlenga, P., Morel, S., Furrer, R., Hostettler, I. C., Bakker, M. K., Bourcier, R., Lindgren, A., Maschke, S., Bozinov, O., Houlden, H., Werring, D., Ruigrok, Y. M., Wostrack, M., Meyer, B., Neidert, M. C., Hirsch, S., & Spinner, G. R. (2026). Mixed-effects additive Bayesian networks for the assessment of ruptured intracranial aneurysms : insights from multicenter data. Computers in Biology and Medicine, 201(111380). https://doi.org/10.1016/j.compbiomed.2025.111380
Difrancesco, S., Bauert, M. M., Lehmann, C., Häsler, S., Zhang, Y., Hirsch, S., Ackermann, P., Stockinger, K., Reif, M., Mathieu, S., Götz, A., Wicki, A., Krauthammer, M., & Witt, C. M. (2025). Collaborative design and development of a patient-centered digital health app for supportive cancer care : participatory study. JMIR Human Factors, 12(e73829). https://doi.org/10.2196/73829
Kirchberger, J., Kunz, D., Perrot, G., Hirsch, S., Leifke, M., Hölz, B., Geissmann, L., Käch, M., Wehrli, S., & Eckstein, J. (2025). An explorative study on movement detection using wearable sensors in acute care hospital patients. Scientific Reports, 15(1), 19941. https://doi.org/10.1038/s41598-025-04340-6
Reichl, J. J., Leifke, M., Wehrli, S., Kunz, D., Geissmann, L., Broisch, S., Illien, M., Wellauer, D., von Dach, N., Diener, S., Manser, V., Herren, V., Angerer, A., Hirsch, S., Hölz, B., & Eckstein, J. (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), 179. https://doi.org/10.1186/s13690-024-01409-y
Morel, S., Hostettler, I. C., Spinner, G. R., Bourcier, R., Pera, J., Meling, T., Alg, V., Houlden, H., Bakker, M., van’t Hof, F., Rinkel, G., Foroud, T., Lai, D., Moomaw, C., Worrall, B., Caroff, J., Constant-dits-Beaufils, P., Karakachoff, M., Rimbert, A., et al. (2022). Intracranial aneurysm classifier using phenotypic factors : an international pooled analysis. Journal of Personalized Medicine, 12(9), 1410. https://doi.org/10.3390/jpm12091410
Mack, I., Juchler, N., Rey, S., Hirsch, S., Hoelz, B., Eckstein, J., & Bielicki, J. (2022). Wearable technologies for pediatric patients with surgical infections : more than counting steps? Biosensors, 12(8), 634. https://doi.org/10.3390/bios12080634
Delucchi, M., Spinner, G., Scutari, M., Bijlenga, P., Morel, S., Friedrich, C. M., Furrer, R., & Hirsch, S. (2022). Bayesian network analysis reveals the interplay of intracranial aneurysm rupture risk factors. Computers in Biology and Medicine, 147(105740). https://doi.org/10.1016/j.compbiomed.2022.105740
Juchler, N., Schilling, S., Bijlenga, P., Kurtcuoglu, V., & Hirsch, S. (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). https://doi.org/10.3389/fneur.2022.809391
Eibl, D., Sievers, M., Eibl, R., Bachmann, M., Walton, S., Keel, N., Richner, G., Stübinger, S., Hirsch, S., Yeretzian, C., Opitz, S. E. W., Heldal, T., & Adlhart, C. (2021). Keeping SARS-CoV-2 out : vaccines, filters, and self-disinfecting textiles. Chimia, 75(3), 215–218. https://doi.org/10.2533/chimia.2021.215
Morel, S., Schilling, S., Diagbouga, M. R., Delucchi, M., Bochaton-Piallat, M.-L., Lemeille, S., Hirsch, S., & Kwak, B. R. (2021). Effects of low and high aneurysmal wall shear stress on endothelial cell behavior : differences and similarities. Frontiers in Physiology, 12(727338). https://doi.org/10.3389/fphys.2021.727338
Borčinová, M., Raschmanová, H., Zamora, I., Looser, V., Marešová, H., Hirsch, S., Kyslík, P., & Kovar, K. (2020). Production and secretion dynamics of prokaryotic Penicillin G acylase in Pichia pastoris. Applied Microbiology and Biotechnology, 104(13), 5787–5800. https://doi.org/10.1007/s00253-020-10669-x
Bakker, M. K., van der Spek, R. A. A., van Rheenen, W., Morel, S., Bourcier, R., Hostettler, I. C., Alg, V. S., van Eijk, K. R., Koido, M., Akiyama, M., Terao, C., Matsuda, K., Walters, R. G., Lin, K., Li, L., Millwood, I. Y., Chen, Z., Rouleau, G. A., Zhou, S., 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), 1303–1313. https://doi.org/10.1038/s41588-020-00725-7
Juchler, N., Schilling, S., Bijlenga, P., Morel, S., Rüfenacht, D., Kurtcuoglu, V., & Hirsch, S. (2020). Shape irregularity of the intracranial aneurysm lumen exhibits diagnostic value. Acta Neurochirurgica, 162(9), 2261–2270. https://doi.org/10.1007/s00701-020-04428-0
Juchler, N., Schilling, S., Glüge, S., Bijlenga, P., Rüfenacht, D., Kurtcuoglu, V., & Hirsch, S. (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), 538–546. https://doi.org/10.1080/21681163.2020.1728579
Detmer, F. J., Mut, F., Slawski, M., Hirsch, S., Bijlenga, P., & Cebral, J. R. (2020). Incorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessment. Acta Neurochirurgica, 162(3), 553–566. https://doi.org/10.1007/s00701-020-04234-8
Detmer, F. J., Lückehe, D., Mut, F., Slawski, M., Hirsch, S., Bijlenga, P., von Voigt, G., & Cebral, J. R. (2020). Comparison of statistical learning approaches for cerebral aneurysm rupture assessment. International Journal of Computer Assisted Radiology and Surgery, 15(1), 141–150. https://doi.org/10.1007/s11548-019-02065-2
Detmer, F. J., Hadad, S., Chung, B. J., Mut, F., Slawski, M., Juchler, N., Kurtcuoglu, V., Hirsch, S., Bijlenga, P., Uchiyama, Y., Fujimura, S., Yamamoto, M., Murayama, Y., Takao, H., Koivisto, T., Frösen, J., & Cebral, J. R. (2019). Extending statistical learning for aneurysm rupture assessment to Finnish and Japanese populations using morphology, hemodynamics, and patient characteristics. Neurosurgical Focus, 47(1). https://doi.org/10.3171/2019.4.FOCUS19145
Detmer, F. J., Fajardo-Jiménez, D., Mut, F., Juchler, N., Hirsch, S., Pereira, V. M., Bijlenga, P., & Cebral, J. R. (2018). External validation of cerebral aneurysm rupture probability model with data from two patient cohorts. Acta Neurochirurgica. https://doi.org/10.1007/s00701-018-3712-8
Bijlenga, P., Gondar, R., Schilling, S., Morel, S., Hirsch, S., Cuony, J., Corniola, M.-V., Perren, F., Rüfenacht, D., & Schaller, K. (2017). PHASES score for the management of intracranial aneurysm. Stroke: A Journal of Cerebral Circulation, 48(8), 2105–2112. https://doi.org/10.1161/STROKEAHA.117.017391
Schneider, M., Hirsch, S., Weber, B., Székely, G., & Menze, B. H. (2015). Joint 3-D vessel segmentation and centerline extraction using oblique Hough forests with steerable filters. Medical Image Analysis, 19(1), 220–249. https://doi.org/10.1016/j.media.2014.09.007
Daheim, C., & Hirsch, S. (2015). Emerging practices in foresight and their use in STI policy. STI Policy Review, 6(2), 24–53.
Gessat, M., Hopf, R., Pollok, T., Russ, C., Frauenfelder, T., Sundermann, S. H., Hirsch, S., Mazza, E., Szekely, G., & Falk, V. (2014). Image-based mechanical analysis of stent deformation : concept and exemplary implementation for aortic valve stents. IEEE Transactions on Biomedical Engineering, 61(1), 4–15. https://doi.org/10.1109/TBME.2013.2273496
Hirsch, S., Burggraf, P., & Daheim, C. (2013). Scenario planning with integrated quantification : managing uncertainty in corporate strategy building. Foresight, 15(5), 363–374. https://doi.org/10.1108/FS-09-2012-0064

Written conference contributions, peer-reviewed

Bijlenga, P., Spinner, G., Scutari, M., Delucchi, M., & Hirsch, S. (2025). Introducing Bayesian analysis for clinicians : sex-associated risk assessment of intracranial aneurysms (G. Esposito, Y. Kaku, M. Sebök, L. Regli, & T. Tsukahara, Eds.; pp. 19–26) [Conference paper]. Springer. https://doi.org/10.1007/978-3-031-89844-0_3
Musio, F., Yang, K., Shit, S., Prabhakar, C., Juchler, N., Menze, B., & Hirsch, S. (2024). Quantitative evaluation of the Circle of Willis vascular architecture in 3D CT and MR angiography [Conference paper]. In P. Nithiarasu & R. Lohner (Eds.), CMBE24: 8th International Conference on Computational & Mathematical Biomedical Engineering (Vol. 2, pp. 563–566). Computational & Mathematical Biomedical Engineering. https://doi.org/10.21256/zhaw-31451
Delucchi, M., Spinner, G., Furrer, R., Bijlenga, P., & Hirsch, S. (2024, June). Insights from a multicenter Bayesian network study for advancing unruptured intracranial aneurysm management. 8th International Conference on Computational and Mathematical Biomedical Engineering (CMBE), Arlington, VA, USA, 24-26 June 2024.
Delucchi, M., Spinner, G. R., Bijlenga, P., Morel, S., Hostettler, I., Werring, D., Wostrack, M., Meyer, B., Bourcier, R., Lindgren, A., Bakker, M. K., Ruigrok, Y. M., Furrer, R., & Hirsch, S. (2023). An explainable multicentric analysis for understanding the aetiology of intracranial aneurysm disease [Conference poster]. Clinical and Translational Neuroscience, 7(4), 46–47. https://doi.org/10.3390/ctn7040039
Delucchi, M., Spinner, G. R., Scutari, M., Bijlenga, P., Morel, S., Friedrich, C. M., & Hirsch, S. (2022). Bayesian networks to disentangle the interplay of intracranial aneurysm rupture risk factors [Conference paper]. In P. Nithiarasu & C. Vergara (Eds.), CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering (Vol. 2022, Issue 1, pp. 22–25). Computational and Mathematical Biomedical Engineering.
Juchler, N., Bijlenga, P., & Hirsch, S. (2022). Modeling the location-dependency of aneurysm shape : a morphometric comparative study [Conference paper]. In P. Nithiarasu & C. Vergara (Eds.), CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering (Vol. 2, pp. 703–705). Computational & Mathematical Biomedical Engineering. https://doi.org/10.21256/zhaw-25388
Dupuy, N., Juchler, N., Morel, S., Kwak, B. R., Hirsch, S., & Bijlenga, P. (2022). Exploring intracranial aneurysm instability markers to improve disease modeling [Conference paper]. In P. Nithiarasu & C. Vergara (Eds.), CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering (Vol. 1, pp. 14–17). Computational and Mathematical Biomedical Engineering. https://doi.org/10.21256/zhaw-25387
Juchler, N., Bijlenga, P., & Hirsch, S. (2022). The role of shape for aneurysm risk assessment [Conference paper]. In P. Nithiarasu & C. Vergara (Eds.), CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering (Vol. 1, pp. 84–86). Computational & Mathematical Biomedical Engineering. https://doi.org/10.21256/zhaw-25386
Spinner, G. R., Delucchi, M., Morel, S., Bijlenga, P., & Hirsch, S. (2022). Survival analysis of intracranial aneurysm rupture to study the influence of clinical risk factors : towards a dynamic disease model [Conference paper]. In P. Nithiarasu & C. Vergara (Eds.), CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering (Vol. 1, pp. 72–75). Computational and Mathematical Biomedical Engineering.
Watanabe, K., Anzai, H., Juchler, N., Hirsch, S., & Ohta, M. (2020). Influence of input image configurations on output of a convolutional neural network to detect cerebral aneurysms [Conference paper]. International Mechanical Engineering Congress and Exposition : Volume 3 - Biomedical and Biotechnology Engineering, 3. https://doi.org/10.1115/IMECE2019-11125
Juchler, N., Schilling, S., Bijlenga, P., Rüfenacht, D., Kurtcuoglu, V., & Hirsch, S. (2019). Understanding morphological irregularity : a rater-based study [Conference paper]. CMBE19 Proceedings, 583.
Juchler, N., Schilling, S., Bijlenga, P., Rüfenacht, D., Kurtcuoglu, V., & Hirsch, S. (2019). Identification of clinically relevant characteristics of intracranial aneurysm morphology. 1. Digital Health Lab Day (Life in Numbers 5), Wädenswil, 3. October 2019.
Schilling, S., Morel, S., Bochaton-Piallat, M.-L., Kwak, B., & Hirsch, S. (2017). Endothelial cell elongation under shear stress : a computational model to consolidate observed cell shape changes [Conference paper]. In P. Nithiarasu & A. M. Robertson (Eds.), 5th International Conference on Computational and Mathematical Biomedical Engineering, CMBE2017 (pp. 850–852). Zeta Computational Resources.
Juchler, N., Schilling, S., Bijlenga, P., Kurtcuoglu, V., & Hirsch, S. (2017). Measuring the perceived morphological complexity of intracranial aneurysms [Conference poster]. Abstract Book, 3rd International SystemsX.ch Conference on Systems Biology, 160. https://doi.org/10.3929/ethz-b-000176201
Juchler, N., Schilling, S., Bijlenga, P., Kurtcuoglu, V., & Hirsch, S. (2016, September 1). Shape-based assessment of intracranial aneurysm disease status – a machine learning approach. All SystemsX.ch Day, Bern, 1 September 2016.
Juchler, N., Schilling, S., Vartan, K., & Hirsch, S. (2016, June 29). What’s ugly? : shape-based analysis of intracranial aneurysms. Latsis Symposium 2016 : Personalized Medicine, Zurich, 27-29 June 2016.
Koltukluoglu, T. S., Binter, C., Tanner, C., Hirsch, S., Kozerke, S., Székely, G., & Laadhari, A. (2015). A partial domain approach to enable aortic flow simulation without turbulent modeling [Conference paper]. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 Part II, 544–551. https://doi.org/10.1007/978-3-319-24571-3_65
Koltukluoglu, T. S., Hirsch, S., Binter, C., Kozerke, S., Szekely, G., & Laadhari, A. (2015). A robust comparison approach of velocity data between MRI and CFD based on divergence-free space projection [Conference paper]. 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 1393–1397. https://doi.org/10.1109/ISBI.2015.7164136
Juchler, N., Ebnöther, U., Schilling, S., Hirsch, S., & Kurtcuoglu, V. (2015, September 15). On the utility of 3D Zernike Moment Invariants to assess aneurysm disease status. All SystemsX.ch Day, Bern, 15 September 2015.
Russ, C., Hopf, R., Sündermann, S. H., Born, S., Hirsch, S., Falk, V., Székely, G., & Gessat, M. (2014). Computational stent placement in transcatheter aortic valve implantation [Conference paper]. Biomedical Simulation, 95–105. https://doi.org/10.1007/978-3-319-12057-7_11
Schneider, M., Hirsch, S., Weber, B., Székely, G., & Menze, B. H. (2014). TGIF : topological gap in-fill for vascular networks [Conference paper]. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 Part II, 89–96. https://doi.org/10.1007/978-3-319-10470-6_12
Russ, C., Hopf, R., Hirsch, S., Sundermann, S., Falk, V., Szekely, G., & Gessat, M. (2013). Simulation of transcatheter aortic valve implantation under consideration of leaflet calcification [Conference paper]. 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 711–714. https://doi.org/10.1109/EMBC.2013.6609599
Hirsch, S., Egger, J., Wanke, I., Kulcsar, Z., & Rüfenacht, D. (2013). Clinical relevance of mechano-biological transduction in intracranial aneurysms : the mediating role of thrombus formation and inflammatory response expressing as aneurysm shape [Conference paper]. CMBE13 : 3rd International Conference on Computational & Mathematical Biomedical Engineering, 107–110.

Other publications

Bührer, L., Bijlenga, P., Delucchi, M., Furrer, R., Spinner, G., & Hirsch, S. (2024, September 3). Modelling the burden of disease of intracanial aneurysms. 6th Digital Health Lab Day, Winterthur, Switzerland, 3 September 2024. https://doi.org/10.21256/zhaw-33654
Gerber, N., Fieseler, L., Hirsch, S., Neutsch, L., Papadopoulou, A., & Smits, T. (2022). Zusammenarbeit und wissenschaftlicher Austausch sind der Schlüssel zu erfolgreicher Forschung : der ZHAW Health Research Hub bringt’s unter einen Hut. Clinicum, 2022(6), 80–81. https://doi.org/10.21256/zhaw-26376
Suter, S., Spinner, G., Hoelz, B., Rey, S., Thanabalasingam, S., Eckstein, J., & Hirsch, S. (2022). Visualization and analysis of wearable health data from COVID-19 patients. arXiv. https://doi.org/10.21256/zhaw-24219
Bakker, M. K., van der Spek, R. A. A., van Rheenen, W., Morel, S., Bourcier, R., Hostettler, I. C., Alg, V. S., van Eijk, K. R., Koido, M., Akiyama, M., Terao, C., Matsuda, K., Walters, R. G., Lin, K., Li, L., Millwood, I. Y., Chen, Z., Rouleau, G. A., Zhou, S., 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), 254. https://doi.org/10.1038/s41588-020-00760-4
Bijlenga, P., Morel, S., Hirsch, S., Schaller, K., & Rüfenacht, D. (2019). Plea for an international Aneurysm Data Bank : description and perspectives. Neurosurgical Focus, 47(1), E17. https://doi.org/10.3171/2019.4.FOCUS19185
Juchler, N., Schilling, S., Vartan, K., & Hirsch, S. (2016, September 15). Shape-based assessment of intracranial aneurysm disease status. ZNZ Symposium 2016, Zurich, 15. September 2016.

Oral conference contributions and abstracts

Bührer, L., Bakker, M., Bijlenga, P., Furrer, R., Hirsch, S., Morel, S., & Spinner, G. (2025, May 16). Bayesian network analysis of SNPs rs11153071 and rs2107597 and clinical risk factors in intracranial aneurysms. 32nd Workshop of the International Stroke Genomics Consortium, Gothenburg, Sweden, 14-16 May 2025.
Musio, F., Juchler, N., Yang, K., Menze, B., & Hirsch, S. (2023, August 18). Circle of Willis configurations in stroke patients. 19th Interdisciplinary Cerebrovascular Symposium, Geneva, Switzerland, 17-19 August 2023.
Melloh, M., & Hirsch, S. (2019). How universities can lead the transformation to digital health. Digital Health Conclave, Bangalore, India, 8 April 2019.
Hirsch, S., & Juchler, N. (2019). Real and assumed insights : statistical models and imaging biomarkers for disease characterization of intracranial aneurysms. 1. Digital Health Lab Day (Life in Numbers 5), Wädenswil, 3. October 2019.
Watanabe, K., Anzai, H., Juchler, N., Hirsch, S., Bijlenga, P., & Ohta, M. (2018). Effect of input image representation for results of neural network to detect cerebral aneurysms. 31st Bioengineering Conference / 2018 Annual Meeting of BED/JSME, Koriyama, Japan, 14-15 December 2018.
Juchler, N., Schilling, S., Watanabe, K., Anzai, H., Rüfenacht, D., Bijlenga, P., Kurtcuoglu, V., & Hirsch, S. (2018, October 4). Clinical data sharing : a data scientist’s perspective. Life in Numbers 4, Wädenswil, 4 October 2018.
Juchler, N., Schilling, S., Philippe, B., Rüfenacht, D., Kurtcuoglu, V., & Hirsch, S. (2018, July 12). Reproducing qualitative irregularity ratings by means of quantitative shape descriptors in intracranial aneurysms. 8th World Congress of Biomechanics (WCB2018), Dublin, Ireland, 8-12 July 2018.
Juchler, N., Schilling, S., Rüfenacht, D., Bijlenga, P., Kurtcuoglu, V., & Hirsch, S. (2018, April 13). Aneurysm shape as a diagnostic tool. Kick-off Event: PhD Network in Data Science, Winterthur, 13. April 2018.
Juchler, N., Schilling, S., Bijlenga, P., Rüfenacht, D., Kurtcuoglu, V., & Hirsch, S. (2018, February 8). Aneurysm shape as a diagnostic tool : a machine learning approach. International Neurovascular Exploratory Workshop (iNEW′2018), Zürich, 7-9 February 2018.
Anzai, H., Juchler, N., Bilenga, P., Rüfenacht, D., Wanke, I., & Hirsch, S. (2018, February 8). Correlation of CFD with wall enhancement. iNEW, Zürich, 8. Februar 2018.
Hirsch, S., Juchler, N., Schilling, S., Bijlenga, P., & Rüfenacht, D. (2018, January). Using machine learning to identify shape biomarkers in intracranial aneurysm. Life Science Zurich Impact, Zürich, 22 January 2018.
Hirsch, S., Juchler, N., Schilling, S., Bijlenga, P., & Rüfenacht, D. (2017, August 30). Big Data : machine learning to identify shape biomarkers in intracranial aneurysm. Annual Meeting of the Swiss Society for Biomedical Engineering (SSBE), Winterthur, 30 August 2017.
Anzai, H., Juchler, N., Ohta, M., Hirsch, S., Rüfenacht, D. A., & Wanke, I. (2017, April 12). Where does CFD identify lesion instability in small aneurysms? CMBE17 : 5th International Conference on Computational and Mathematical Biomedical Engineering.
Juchler, N., Schilling, S., Wanke, I., Rüfenacht, D., Bijlenga, P., Kurtcuoglu, V., & Hirsch, S. (2017, April 12). Using shape descriptors to categorize intracranial aneurysms. CMBE17 : 5th International Conference on Computational and Mathematical Biomedical Engineering.
Juchler, N., Schilling, S., Wanke, I., Rüfenacht, D., Bijlenga, P., Kurtcuoglu, V., & Hirsch, S. (2016, June 9). Shape-based modeling of aneurysmal disease status. ECCOMAS Congress 2016, Heraklion, Greece, 5-10 June 2016.
Egger, J., Szczerba, D., Rüfenacht, D., Szekely, G., & Hirsch, S. (2015). The role of clot maturation inside intracranial aneurysms using a viscoelastic thrombosis model. 9th European Solid Mechanics Conference (ESMC), Madrid, Spain, 6-10 July 2015.
Bijlenga, P., & Hirsch, S. (2015). Intracranial aneurysms rupture risk clinical assessment. 9th European Solid Mechanics Conference (ESMC), Madrid, Spain, 6-10 July 2015.
Neufeld, E., Wissmann, P., Szczerba, D., Teixeira, F., Hirsch, S., & Kuster, N. (2015). Computational framework for personalized characterization of aneurysm physics and physiology, as well as disease progression modelling. 9th European Solid Mechanics Conference (ESMC), Madrid, Spain, 6-10 July 2015.
Egger, J., Szczerba, D., Rüfenacht, D., Szekely, G., & Hirsch, S. (2014). 2D viscoelastic thrombosis model for stented aneurysms. 7th World Congress of Biomechanics, Boston, USA, 06-11 July 2014.

Research data

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

Affiliations

Current Affiliations

Stiftung Insel Hombroich: Member of the the Board of Trustees
I am the Representative of the Sciences on the Board of Trustees of Stiftung Insel Hombroich. Hombroich is the dynamic and diverse interplay of art, nature, buildings, collections, archives and people. The Hombroich site connects artists, scientists, foundation staff, volunteers, and associated institutions. Along with Museum Insel Hombroich, the parent foundation Stiftung Insel Hombroich possesses two further terrains and their architectural ensembles, which enter into diverse relationships with their natural environment and which each have a character of their own. — These are the Raketenstation Hombroich and the Kirkeby-Feld., Neuss
09 / 2018 - 12 / 2030

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