Machine Learning for Automatic Prediction of the Quality of Electrophysiological Recordings

The quality of electrophysiological recordings varies a lot due to technical and biological variability and neuroscientists inevitably have to select “good” recordings for further analyses. This procedure is time-consuming and prone to selection biases. Here, we investigate replacing human decisions...

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Detalles Bibliográficos
Autores principales: Nowotny, Thomas, Rospars, Jean-Pierre, Martinez, Dominique, Elbanna, Shereen, Anton, Sylvia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3851757/
https://www.ncbi.nlm.nih.gov/pubmed/24324634
http://dx.doi.org/10.1371/journal.pone.0080838

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3851757/
https://www.ncbi.nlm.nih.gov/pubmed/24324634
http://dx.doi.org/10.1371/journal.pone.0080838

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