CEIEC researchers Ana Maria Maitín, Alberto Nogales and Álvaro García Tejedor have published the article “EEGraph: An open-source Python library for modeling electroencephalograms using graphs” in the journal Neurocomputing. This article describes the EEGraph Python library which allows modeling electroencephalograms […]
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New paper published: BERT learns about Parkinson disease
We have a new publication, in this case, we have used BERT, a well-known model in Natural Language Processing, to diagnose Parkinson’s. This is the first time that BERT has been adapted to manage brain signals obtaining accuracies near to […]
CEIEC sends a poster to the MDS Congress
CEIEC has submitted a poster to the MDS conference on a biomarker based on natural language processing methods to detect the stages of Parkinson’s disease through the use of electroencephalograms.
Survey of Machine Learning Techniques in the Analysis of EEG Signals for Parkinson’s Disease: A Systematic Review
An article by Ana M. Maitín López and Álvaro J. García Tejedor, members of the CEIEC research team, and Juan Pablo Romero Muñoz, lecturer at the UFV and member of the Brain Injury Unit of the Beata María Ana Hospital, […]
Machine Learning Approaches for Detecting Parkinson’s Disease from EEG Analysis
A research paper has recently been published in the Applied Sciences journal by Ana M. Maitín López and Álvaro J. García Tejedor, members of the CEIEC research group, and Juan Pablo Romero Muñoz, professor at the UFV and member of […]