Novel artificial intelligence-based hypodensity detection tool improves clinician identification of hypodensity on non-contrast computed tomography in stroke patients

Novel artificial intelligence-based hypodensity detection tool improves clinician identification of hypodensity on non-contrast computed tomography in stroke patients

IntroductionIn acute stroke, identifying early changes (parenchymal hypodensity) on non-contrast CT (NCCT) can be challenging. We aimed to identify whether the accuracy of clinicians in detecting acute hypodensity in ischaemic stroke patients on a non-contrast CT is improved with the use of an Artif...

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Bibliographic Details
Main Authors: Angela Dos Santos, Milanka Visser, Longting Lin, Andrew Bivard, Leonid Churilov, Mark William Parsons
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-02-01
Series:Frontiers in Neurology
Subjects:
automated hypodensity detection tools
artificial intelligence
machine learning
acute ischaemic stroke
treatment
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2024.1359775/full

Internet

https://www.frontiersin.org/articles/10.3389/fneur.2024.1359775/full

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