Predicting Mortality after Transcatheter Aortic Valve Replacement using Preprocedural CT [Scientific Reports 2024]
-
Updated
May 5, 2026 - Python
#
tavr
Here are 3 public repositories matching this topic...
Interpretable machine learning framework for predicting mid-term mortality and major periprocedural complications after transcatheter aortic valve implantation (TAVI) using pre-procedural clinical, echocardiographic, CT, and cusp-specific aortic valve calcium topography data. Includes reproducible survival and classification pipelines following TRI
machine-learning scikit-learn medical-imaging survival-analysis radiology calcium computed-tomography tavi cardiology explainable-ai shap cardiovascular-medicine scikit-survival tavr aortic-valve transcatheter-aortic-valve-implantation
-
Updated
Jul 10, 2026 - Python
Extract coronary/aortic calcification from cardiac CT while keeping the metallic stent mask separate — HU-threshold based, computed inside NIfTI segmentation masks (aorta/LV/coronary).
-
Updated
Jun 6, 2026 - Python
Improve this page
Add a description, image, and links to the tavr topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the tavr topic, visit your repo's landing page and select "manage topics."