Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS) Severity

In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven) regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers...

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Detalles Bibliográficos
Autores principales: Bosch-Bayard, Jorge, Galán-García, Lídice, Fernandez, Thalia, Lirio, Rolando B., Bringas-Vega, Maria L., Roca-Stappung, Milene, Ricardo-Garcell, Josefina, Harmony, Thalía, Valdes-Sosa, Pedro A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5775224/
https://www.ncbi.nlm.nih.gov/pubmed/29379411
http://dx.doi.org/10.3389/fnins.2017.00749

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5775224/
https://www.ncbi.nlm.nih.gov/pubmed/29379411
http://dx.doi.org/10.3389/fnins.2017.00749

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