HAL (France)
open access
Physics Constrained Graph Neural Network for Real Time Prediction of Intracranial Aneurysm Hemodynamics
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Multiphysics learning with graph neural networks for thrombosis prediction in intracranial aneurysms#322607
- Safety and EffecTiveness of the Silk Vista Flow DiverteR in the TrEatment of Unruptured IntracrAnial AneurysMs#876927
- Time-to-event ensemble machine learning approach for predicting long-term survival of abdominal aortic aneurysm patients undergoing endovascular aneurysm repair#275940
- Time-to-event ensemble machine learning approach for predicting long-term survival of abdominal aortic aneurysm patients undergoing endovascular aneurysm repair.#275744
- Stellate Ganglion Block in Preventing Cerebral Vasospasm Secondary to Subarachnoid Hemorrhage#1115034
Record · ID 322606
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive