Machine Learning–Enabled Detection of Unruptured Cerebral Aneurysms Improves Detection Rates and Clinical Care

Machine Learning–Enabled Detection of Unruptured Cerebral Aneurysms Improves Detection Rates and Clinical Care

Background Unruptured cerebral aneurysms (UCAs) have a relatively low prevalence of ≈3%, but detection can prevent devastating consequences of subarachnoid hemorrhage. Here, we assess the performance of a machine learning algorithm to identify UCAs and determine whether routine use of the algorithm...

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Bibliographic Details
Main Authors: Hyun‐Woo Kim, Anjan Ballekere, Iman Ali, Sergio Salazar Marioni, Rania Abdelkhaleq, Arash Niktabe, Hussain Azeem, Ananya Iyyangar, Omri Segev, Orin Bibas, Dan Paz, Christopher J. Love, Luca Giancardo, Sunil A. Sheth
Format: Article
Language:English
Published: Wiley 2023-11-01
Series:Stroke: Vascular and Interventional Neurology
Subjects:
cerebral aneurysm
CT scans
machine learning
neuroIntervention
radiology
Online Access:https://www.ahajournals.org/doi/10.1161/SVIN.123.000938

Internet

https://www.ahajournals.org/doi/10.1161/SVIN.123.000938

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