Machine Learning-Based Prediction of Stroke in Emergency Departments
Vida Abedi,
Debdipto Misra,
Durgesh Chaudhary
et al.
Abstract:Background: Stroke misdiagnosis, associated with poor outcomes, is estimated to occur in 9% of all stroke patients. Objectives: We hypothesized that machine learning (ML) could assist in the diagnosis of ischemic stroke in emergency departments (EDs). Design: The study was conducted and reported according to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis guidelines. We performed model development and prospective temporal validation, using data from pre- and … Show more
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