Development and validation of an explainable machine learning prediction model of hemorrhagic transformation after intravenous thrombolysis in stroke
ObjectiveTo develop and validate an explainable machine learning (ML) model predicting the risk of hemorrhagic transformation (HT) after intravenous thrombolysis.MethodsWe retrospectively enrolled patients who received intravenous tissue plasminogen activator (IV-tPA) thrombolysis within 4.5 h after...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Neurology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fneur.2024.1446250/full |
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