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Artificial intelligence for detecting traumatic intracranial haemorrhage with CT: A workflow-oriented implementation
Selim Abed1, Klaus Hergan1, Johannes Pfaff2
1Department of Radiology, University Hospital Salzburg, Paracelsus Medical University, Austria.
Abstract:
The objective of this study was to assess the performance of an artificial intelligence (AI) algorithm in detecting intracranial haemorrhages (ICHs) on non-contrast CT scans (NCCT). Another objective was to gauge the department's acceptance of said algorithm. Surveys conducted at three and nine months post-implementation revealed an increase in radiologists' acceptance of the AI tool with an increasing performance. However, a significant portion still preferred an additional physician given comparable cost. Our findings emphasize the importance of careful software implementation into a robust IT architecture.
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