This study aims to validate a machine learning model that stratifies the risk of stroke in patients who present to the emergency department with dizziness or vertigo.
This is a cross-sectional, hospital-based study, with no randomization procedure. Over a 21-month period, approximately 600 subjects will be enrolled. The study will assess the risk of stroke in each patient using a machine-learning model. To detect ischemic or hemorrhagic stroke, each patient will undergo a non-contrast brain magnetic resonance imaging study. The predictive performance of the machine-learning model will be evaluated in terms of accuracy, precision, recall, F1 score, and area under the receiver operating characteristics curve.
Study Type
OBSERVATIONAL
Enrollment
600
Brain magnetic resonance imaging
Number of participants with stroke
Number of participants with ischemic or hemorrhagic stroke confirmed by brain magnetic resonance imaging
Time frame: Between 24 hours and 14 days after the emergency department visit
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