A comparison of machine learning classifiers for pediatric epilepsy using resting-state functional MRI latency data

Epilepsy affects 1 in 150 children under the age of 10 and is the most common chronic pediatric neurological condition; poor seizure control can irreversibly disrupt normal brain development. The present study compared the ability of different machine learning algorithms trained with resting-state f...

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Detalles Bibliográficos
Autores principales: Nguyen, Ryan D., Smyth, Matthew D., Zhu, Liang, Pao, Ludovic P., Swisher, Shannon K., Kennady, Emmett H., Mitra, Anish, Patel, Rajan P., Lankford, Jeremy E., Von Allmen, Gretchen, Watkins, Michael W., Funke, Michael E., Shah, Manish N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2021
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8330002/
https://www.ncbi.nlm.nih.gov/pubmed/34405049
http://dx.doi.org/10.3892/br.2021.1453

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8330002/
https://www.ncbi.nlm.nih.gov/pubmed/34405049
http://dx.doi.org/10.3892/br.2021.1453

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