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Machine Learning Models to Predict Electroencephalographic Seizures in Critically Ill Children
OBJECTIVE: Determine whether machine learning techniques would enhance our ability to incorporate key variables into a parsimonious model with optimized prediction performance for electroencephalographic seizure (ES) prediction in critically ill children. METHODS: We analyzed data from a prospective...
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| Published in: | Seizure |
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| Main Authors: | , , , , , , , , |
| Format: | Artigo |
| Language: | Inglês |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8044039/ https://ncbi.nlm.nih.gov/pubmed/33714840 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.seizure.2021.03.001 |
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