Mostrando 4 resultados de: 4
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(2)
Neurocomputing(1)
PLoS ONE(1)
A hybrid unsupervised-Deep learning tandem for electrooculography time series analysis
ArticleAbstract: Medical data are often tricky to get mined for patterns even by the generally demonstrated successfuPalabras claves:Autores:Atencia M., Becerra-García R.A., García-Lagos F., Joya-Caparrós G., Rodolfo García−Bermúdez, Stoean C., Stoean R., Velazquez-Perez L.Fuentes:scopusData mining process for identification of non-spontaneous saccadic movements in clinical electrooculography
ArticleAbstract: In this paper we evaluate the use of the machine learning algorithms Support Vector Machines (SVM),Palabras claves:Classification and regression trees, Clinical electrooculography, K-NEAREST NEIGHBORS, Saccade identification, SUPPORT VECTOR MACHINESAutores:Becerra-García R.A., Cuevas-Beltrán F.R., Fernández-Higuera A., García-Lagos F., Joya-Caparrós G., Rodolfo García−Bermúdez, Rodráguez-Labrada R., Velázquez-Mariño M., Velázquez-Rodríguez C.Fuentes:scopusNon spontaneous saccadic movements identification in clinical electrooculography using machine learning
Conference ObjectAbstract: In this paper we evaluate the use of the machine learning algorithms Support Vector Machines (SVM),Palabras claves:classification, Clinical electrooculography, Saccade identificationAutores:Becerra-García R.A., Cuevas-Beltrán F.R., Fernández-Higuera A., García-Lagos F., Joya-Caparrós G., Rodolfo García−Bermúdez, Rodríguez-Labrada R., Velázquez-Mariño M., Velázquez-Rodríguez C.Fuentes:scopusUnsupervised Learning as a Complement to Convolutional Neural Network Classification in the Analysis of Saccadic Eye Movement in Spino-Cerebellar Ataxia Type 2
Conference ObjectAbstract: This paper aims at assessing spino-cerebellar type 2 ataxia by classifying electrooculography recorPalabras claves:classification, convolutional neural networks, K-Means, Saccadic eye movement, Self-Organizing Maps, unsupervised learningAutores:Atencia M., Becerra-García R.A., García-Lagos F., Joya-Caparrós G., Rodolfo García−Bermúdez, Stoean C., Stoean R., Velazquez-Perez L.Fuentes:scopus