Showing results 1 to 20 of 32
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| Issue Date | Title | Involved Person(s) |
| 13-Apr-2018 | Aneurysm shape as a diagnostic tool | Juchler, Norman; Schilling, Sabine; Rüfenacht, Daniel; Bijlenga, Philippe; Kurtcuoglu, Vartan, et al |
| 8-Feb-2018 | Aneurysm shape as a diagnostic tool : a machine learning approach | Juchler, Norman; Schilling, Sabine; Bijlenga, Philippe; Rüfenacht, Daniel; Kurtcuoglu, Vartan, et al |
| 26-Jun-2022 | AneuX morphology database | Juchler, Norman; Bijlenga, Philippe; Hirsch, Sven |
| Feb-2021 | Author Correction: Genome-wide association study of intracranial aneurysms identifies 17 risk loci and genetic overlap with clinical risk factors | Bakker, Mark K.; van der Spek, Rick A. A.; van Rheenen, Wouter; Morel, Sandrine; Bourcier, Romain, et al |
| 20-Jun-2022 | Bayesian network analysis reveals the interplay of intracranial aneurysm rupture risk factors | Delucchi, Matteo; Spinner, Georg; Scutari, Marco; Bijlenga, Philippe; Morel, Sandrine, et al |
| 2022 | Bayesian networks to disentangle the interplay of intracranial aneurysm rupture risk factors | Delucchi, Matteo; Spinner, Georg Ralph; Scutari, Marco; Bijlenga, Philippe; Morel, Sandrine, et al |
| 30-Aug-2017 | Big Data : machine learning to identify shape biomarkers in intracranial aneurysm | Hirsch, Sven; Juchler, Norman; Schilling, Sabine; Bijlenga, Philippe; Rüfenacht, Daniel |
| 4-Oct-2018 | Clinical data sharing : a data scientist's perspective | Juchler, Norman; Schilling, Sabine; Watanabe, Kazuhiro; Anzai, Hitomi; Rüfenacht, Daniel, et al |
| Jan-2020 | Comparison of statistical learning approaches for cerebral aneurysm rupture assessment | Detmer, Felicitas J.; Lückehe, Daniel; Mut, Fernando; Slawski, Martin; Hirsch, Sven, et al |
| 2018 | Effect of input image representation for results of neural network to detect cerebral aneurysms | Watanabe, Kazuhiro; Anzai, Hitomi; Juchler, Norman; Hirsch, Sven; Bijlenga, Philippe, et al |
| 2022 | Exploring intracranial aneurysm instability markers to improve disease modeling | Dupuy, Nicolas; Juchler, Norman; Morel, Sandrine; Kwak, Brenda R.; Hirsch, Sven, et al |
| Jul-2019 | Extending statistical learning for aneurysm rupture assessment to Finnish and Japanese populations using morphology, hemodynamics, and patient characteristics | Detmer, Felicitas J.; Hadad, Sara; Chung, Bong Jae; Mut, Fernando; Slawski, Martin, et al |
| 30-Oct-2018 | External validation of cerebral aneurysm rupture probability model with data from two patient cohorts | Detmer, Felicitas J.; Fajardo-Jiménez, Daniel; Mut, Fernando; Juchler, Norman; Hirsch, Sven, et al |
| 16-Nov-2020 | Genome-wide association study of intracranial aneurysms identifies 17 risk loci and genetic overlap with clinical risk factors | Bakker, Mark K.; van der Spek, Rick A. A.; van Rheenen, Wouter; Morel, Sandrine; Bourcier, Romain, et al |
| 2019 | Identification of clinically relevant characteristics of intracranial aneurysm morphology | Juchler, Norman; Schilling, Sabine; Bijlenga, Philippe; Rüfenacht, Daniel; Kurtcuoglu, Vartan, et al |
| 1-Feb-2020 | Incorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessment | Detmer, Felicitas J.; Mut, Fernando; Slawski, Martin; Hirsch, Sven; Bijlenga, Philippe, et al |
| 2022 | Intracranial aneurysm classifier using phenotypic factors : an international pooled analysis | Morel, Sandrine; Hostettler, Isabel C.; Spinner, Georg R.; Bourcier, Romain; Pera, Joanna, et al |
| 2015 | Intracranial aneurysms rupture risk clinical assessment | Bijlenga, Philippe; Hirsch, Sven |
| 7-Sep-2017 | Measuring the perceived morphological complexity of intracranial aneurysms | Juchler, Norman; Schilling, Sabine; Bijlenga, Philippe; Kurtcuoglu, Vartan; Hirsch, Sven |
| 2022 | Modeling the location-dependency of aneurysm shape : a morphometric comparative study | Juchler, Norman; Bijlenga, Philippe; Hirsch, Sven |
