Machine Learning-Based Prediction of Stroke in Emergency Departments

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 acc...

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Bibliographic Details
Published in:	Therapeutic advances in neurological disorders Vol. 17; p. 17562864241239108
Main Authors:	Abedi, Vida, Misra, Debdipto, Chaudhary, Durgesh, Avula, Venkatesh, Schirmer, Clemens M., Li, Jiang, Zand, Ramin
Format:	Journal Article
Language:	English
Published:	London, England SAGE Publications 01.01.2024 SAGE PUBLICATIONS, INC SAGE Publishing
Subjects:	Diagnosis Electronic health records Electronic medical records Emergency medical care Ischemia Learning algorithms Machine learning Original Research Patients Prediction models Stroke natural language processing emergency department machine learning artificial intelligence ischemic stroke
ISSN:	1756-2864, 1756-2856, 1756-2864
Online Access:	Get full text
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