Deep learning for neonatal seizure detection: a friend rather than foe

Affiliations

¹ Paediatric Neurology and Muscular Diseases Unit, G Gaslini Institute, Genova, Italy; Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genova, Italy. Electronic address: strianop@gmail.com.
² Paediatric Neurology and Muscular Diseases Unit, G Gaslini Institute, Genova, Italy; Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genova, Italy.

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Pasquale Striano et al. Lancet Child Adolesc Health. 2020 Oct.

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. 2020 Oct;4(10):711-712.

doi: 10.1016/S2352-4642(20)30242-X. Epub 2020 Aug 27.

¹ Paediatric Neurology and Muscular Diseases Unit, G Gaslini Institute, Genova, Italy; Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genova, Italy. Electronic address: strianop@gmail.com.
² Paediatric Neurology and Muscular Diseases Unit, G Gaslini Institute, Genova, Italy; Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genova, Italy.

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A machine-learning algorithm for neonatal seizure recognition: a multicentre, randomised, controlled trial.
Pavel AM, Rennie JM, de Vries LS, Blennow M, Foran A, Shah DK, Pressler RM, Kapellou O, Dempsey EM, Mathieson SR, Pavlidis E, van Huffelen AC, Livingstone V, Toet MC, Weeke LC, Finder M, Mitra S, Murray DM, Marnane WP, Boylan GB. Pavel AM, et al. Lancet Child Adolesc Health. 2020 Oct;4(10):740-749. doi: 10.1016/S2352-4642(20)30239-X. Epub 2020 Aug 27. Lancet Child Adolesc Health. 2020. PMID: 32861271 Free PMC article. Clinical Trial.