Abstract Number ‐ 245: Machine Learning‐Enabled Detection of Unruptured Cerebral Aneurysms Improves Detection Rates and Clinical Care
Introduction Unruptured cerebral aneurysms (UCAs) have a relatively low prevalence of approximately 3%, but detection can prevent devastating consequences of subarachnoid hemorrhage. Here, we assess the performance of a machine‐learning (ML) algorithm to identify UCAs and determine whether routine u...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-03-01
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| Series: | Stroke: Vascular and Interventional Neurology |
| Online Access: | https://www.ahajournals.org/doi/10.1161/SVIN.03.suppl_1.245 |