دورية أكاديمية
Reinforcement learning for patient-specific optimal stenting of intracranial aneurysms
| العنوان: | Reinforcement learning for patient-specific optimal stenting of intracranial aneurysms |
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| المؤلفون: | E. Hachem, P. Meliga, A. Goetz, P. Jeken Rico, J. Viquerat, A. Larcher, R. Valette, A. F. Sanches, V. Lannelongue, H. Ghraieb, R. Nemer, Y. Ozpeynirci, T. Liebig |
| المصدر: | Scientific Reports, Vol 13, Iss 1, Pp 1-16 (2023) |
| بيانات النشر: | Nature Portfolio, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Medicine LCC:Science |
| مصطلحات موضوعية: | Medicine, Science |
| الوصف: | Abstract Developing new capabilities to predict the risk of intracranial aneurysm rupture and to improve treatment outcomes in the follow-up of endovascular repair is of tremendous medical and societal interest, both to support decision-making and assessment of treatment options by medical doctors, and to improve the life quality and expectancy of patients. This study aims at identifying and characterizing novel flow-deviator stent devices through a high-fidelity computational framework that combines state-of-the-art numerical methods to accurately describe the mechanical exchanges between the blood flow, the aneurysm, and the flow-deviator and deep reinforcement learning algorithms to identify a new stent concepts enabling patient-specific treatment via accurate adjustment of the functional parameters in the implanted state. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2045-2322 |
| Relation: | https://doaj.org/toc/2045-2322 |
| DOI: | 10.1038/s41598-023-34007-z |
| URL الوصول: | https://doaj.org/article/a51b4a02a8264d78b234903e10039a6e |
| رقم الأكسشن: | edsdoj.51b4a02a8264d78b234903e10039a6e |
| قاعدة البيانات: | Directory of Open Access Journals |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 20452322 |
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| DOI: | 10.1038/s41598-023-34007-z |