A paper entitled: “A systematic review of electroencephalography open datasets and its usage with deep learning models” has been accepted for publication by the IEEE Access Journal (Q2). This paper co-authored by Alberto Nogales Moyano and Alvaro José García Tejedor compiles a set […]
Category: Álvaro García Tejedor
New article published: Audio Restoration using Deep Autoencoders
A new publication in the lab. In this case, Alberto Nogales Moyano and Alvaro José García Tejedor have published a paper entitled: “A Deep Learning framework for audio restoration using Convolutional/Deconvolutional Deep Autoencoders” in the journal Expert systems with applications. […]
New article published: DL on Infantile Epileptic Spasms
Journal “Computer Methods and Programs in Biomedicine” (Q1 in Computer Science) has accepted a paper entitled “Discriminating and understanding brain states in children with epileptic spasms using deep learning and graph metrics analysis of brain connectivity“. In this paper co-authored […]
New publication: DL on Abdominal Aortic Aneurysms
First paper of the year published by Alvaro José García Tejedor and Alberto Nogales Moyano and co-authored with angiovascular surgeon Fernando Gallardo and former CEIEC intern Miguel Pajares Hernández. In this paper titled “A semiautomatic method for obtaining a predictive deep learning model and a rule-based system […]
New publication: EEGraph
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 […]
New publication: RASFF network explained
A new of our papers has been accepted by the Food Control journal (Q1). CEIEC researchers Alvaro José García Tejedor and Alberto Nogales Moyano with the collaboration of Marçal Mora Cantallops from Universidad de Alcalá and former researcher Rodrigo Díaz […]
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.
UFV signs a collaboration agreement with ADAMO Robot
The UFV has signed an agreement with ADAMO Robot to carry out activities that promote the creation of new training projects, research, internships, employment and transfer of research results. Finding new treatments for musculoskeletal pain has become a priority and […]
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, […]