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A Machine Learning Approach to Investigate the Relationship between Shape Features and Numerically Predicted Risk of Ascending Aortic Aneurysm
Geometric features of the aorta are linked to patient risk of rupture in the clinical decision to electively repair an ascending aortic aneurysm (AsAA). Previous approaches have focused on relationship between intuitive geometric features (e.g. diameter and curvature) and wall stress. This work inve...
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| Pubblicato in: | Biomech Model Mechanobiol |
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| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2017
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5630492/ https://ncbi.nlm.nih.gov/pubmed/28386685 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s10237-017-0903-9 |
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