Dr. Norman Juchler

Dr. Norman Juchler

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

+41 58 934 56 87
norman.juchler@zhaw.ch

Netzwerk

Mitglied in Netzwerken

ORCID digital identifier

ORCID ID: 0000-0001-8518-7211

Projekte

Aufbau einer vertrauenswürdigen Forschungsumgebung für klinische KI und digitale Zwillinge in der Orthopädie / Stellv. Projektleiter:in / laufend
GEMINI: Mehrskalige digitale Zwillinge (Digital Twins) für Patient:innen mit ischämischem oder hämorrhagischem Schlaganfall / Stellv. Projektleiter:in / laufend
Stroke DynamiX – Graphische und kausale Netzwerke für das personalisierte Schlaganfallmanagement / Teammitglied / abgeschlossen
OSR4H – Open Set Recognition for Hematology / Teammitglied / abgeschlossen
Deep Brain Vessel Profiler / Teammitglied / abgeschlossen
Smart Hospital – Integrated Framework, Tools & Solutions / Teammitglied / abgeschlossen
Die Exploration der Gen-Harmonisierung / Teammitglied / abgeschlossen
AneuX Modeling – Shape as a Biomarker for Instability of Intracranial Aneurysms / Teammitglied / abgeschlossen
Intracranial Aneurysm Database / Teammitglied / abgeschlossen

Publikationen

Beiträge in wissenschaftlicher Zeitschrift, peer-reviewed

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.
Reissenberger, P. et al. (2023) 'Determine atrial fibrillation burden with a photoplethysmographic mobile sensor: the atrial fibrillation burden trial : detection and quantification of episodes of atrial fibrillation using a cloud analytics service connected to a wearable with photoplethysmographic sensor', European Heart Journal - Digital Health, 4(5), pp. 402–410. doi: 10.1093/ehjdh/ztad039.
Bächinger, D. et al. (2023) 'Radiological feature heterogeneity supports etiological diversity among patient groups in Meniere's disease', Scientific Reports, 13(1), p. 10303. doi: 10.1038/s41598-023-36479-5.
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.
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.
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. (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.

Bücher, peer-reviewed

Juchler, N. (2020) Shape-based analysis of intracranial aneurysms. Doctoral dissertation. University of Zurich. doi: 10.5167/uzh-200995.

Schriftliche Konferenzbeiträge, peer-reviewed

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) '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.
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.
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) '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.
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. (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.
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.

Weitere Publikationen

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

Musio, F. et al. (2023) 'Circle of Willis configurations in stroke patients', in 19th Interdisciplinary Cerebrovascular Symposium, Geneva, Switzerland, 17-19 August 2023.
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.
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.
Anzai, H. et al. (2018) 'Correlation of CFD with wall enhancement', in iNEW, Zürich, 8. Februar 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.