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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.
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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.
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600 participants in 1 patient group
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Sheng-Feng Sung, MD, PhD
Data sourced from clinicaltrials.gov
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