Machine learning for predicting outcomes of transcatheter aortic valve implantation: A systematic review
<h3>Background</h3><p dir="ltr">Transcatheter aortic valve implantation (TAVI) therapy has demonstrated its clear benefits such as low invasiveness, to treat aortic stenosis. Despite associated benefits, still post-procedural complications might occur. The severity of the...
محفوظ في:
| المؤلف الرئيسي: | Ruba Sulaiman (17734065) (author) |
|---|---|
| مؤلفون آخرون: | Md.Ahasan Atick Faisal (20837645) (author), Maram Hasan (6672440) (author), Muhammad E.H. Chowdhury (17151154) (author), Faycal Bensaali (12427401) (author), Abdulrahman Alnabti (20667683) (author), Huseyin C. Yalcin (6695099) (author) |
| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
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مواد مشابهة
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Machine learning for predicting outcomes of transcatheter aortic valve implantation: A systematic review
حسب: Ruba, Sulaiman
منشور في: (2025) -
Outcomes of the Qatar Transcatheter aortic valve implantation- registry (QATAVI-registry) –first report 24/7/2024
حسب: Abdulrahman, Alnabti
منشور في: (2025) -
Latest Developments in Adapting Deep Learning for Assessing TAVR Procedures and Outcomes
حسب: Anas M. Tahir (16870077)
منشور في: (2023) -
Outcomes of the Transcatheter aortic valve implantation- registry (QATAVI-registry) –first report 24/7/2024
حسب: Abdulrahman Alnabti (20667683)
منشور في: (2025) -
Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling
حسب: Armin, Amindari
منشور في: (2017)