Machine learning for forecasting initial seizure onset in neonatal hypoxic-ischemic encephalopathy.
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| Title: | Machine learning for forecasting initial seizure onset in neonatal hypoxic-ischemic encephalopathy. |
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| Authors: | Bernardo D; Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA., Kim J; Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, California, USA., Cornet MC; Department of Pediatrics, University of California, San Francisco, San Francisco, California, USA., Numis AL; Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA., Scheffler A; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA., Rao VR; Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA., Amorim E; Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA., Glass HC; Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA.; Department of Pediatrics, University of California, San Francisco, San Francisco, California, USA.; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA. |
| Source: | Epilepsia [Epilepsia] 2025 Jan; Vol. 66 (1), pp. 89-103. Date of Electronic Publication: 2024 Nov 04. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Blackwell Science Country of Publication: United States NLM ID: 2983306R Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1528-1167 (Electronic) Linking ISSN: 00139580 NLM ISO Abbreviation: Epilepsia Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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