Machine Learning Modeling to Predict Atrial Fibrillation Detection in Embolic Stroke of Undetermined...
Machine Learning Modeling to Predict Atrial Fibrillation Detection in Embolic Stroke of Undetermined Source Patients
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Switzerland: MDPI AG
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Language
English
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Switzerland: MDPI AG
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Background: In patients with embolic stroke of undetermined source (ESUS), occult atrial fibrillation (AF) has been implicated as a key source of cardioembolism. However, only a minority acquire implantable cardiac loop recorders (ILRs) to detect occult paroxysmal AF, partly due to financial cost and procedural inconvenience. Without the initiation...
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Machine Learning Modeling to Predict Atrial Fibrillation Detection in Embolic Stroke of Undetermined Source Patients
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TN_cdi_proquest_miscellaneous_3060371613
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_3060371613
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ISSN
2075-4426
E-ISSN
2075-4426
DOI
10.3390/jpm14050534
