Artificial Intelligence Triage of Urgent Versus Non-Urgent CT Brain Findings to Support Expedited Emergency Department Disposition: A Retrospective Validation Study.
OBJECTIVE: Evaluate the diagnostic accuracy of an artificial intelligence (AI) model for identifying urgent computed tomography brain (CTB) findings in consecutive emergency department (ED) patients and estimate the prop Preliminary results provide the safety rationale to proceed with a prospective trial aiming to incorporate this technology into ED workflows. Full text review required for further details.
OBJECTIVE: Evaluate the diagnostic accuracy of an artificial intelligence (AI) model for identifying urgent computed tomography brain (CTB) findings in consecutive emergency department (ED) patients and estimate the prop Preliminary results provide the safety rationale to proceed with a prospective trial aiming to incorporate this technology into ED workflows. Full text review required for further details.
What the study was
- Study design
- Diagnostic Validation Study
- Population
- Patient/participant population (size not extracted)
- Category
- Genomics/Precision Medicine
- Maturity
- Validated
- Journal
- Emergency medicine Australasia : EMA
Why it surfaced
Scored 8/10 (Diagnostic Validation Study; novelty=2, relevance=3, design_quality=2, population_or_unmet_need=1). HIGH priority.
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