Mapping differential responses to cognitive training using machine learning

We used two simple unsupervised machine learning techniques to identify differential trajectories of change in children who undergo intensive working memory (WM) training. We used self‐organizing maps (SOMs)—a type of simple artificial neural network—to represent multivariate cognitive training data...

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Detalles Bibliográficos
Autores principales: Rennie, Joseph P., Zhang, Mengya, Hawkins, Erin, Bathelt, Joe, Astle, Duncan E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Special Issue Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314597/
https://www.ncbi.nlm.nih.gov/pubmed/31125497
http://dx.doi.org/10.1111/desc.12868

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314597/
https://www.ncbi.nlm.nih.gov/pubmed/31125497
http://dx.doi.org/10.1111/desc.12868

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