Unsupervised learning: application to epilepsy

Translated title of the contribution: Unsupervised learning: application to epilepsy

Gabriel Mauricio Martínez-Toro, Dewar Rico-Bautista, Efrén Romero-Riaño, Paola Andrea Romero-Riaño

Research output: Articles / NotesScientific Articlepeer-review


Epilepsy is a neurological disorder characterized by recurrent seizures. The primary objective is to present an analysis of the results shown in the training data simulation charts. Data were collected by means of the 10-20 system. The “10–20” system is an internationally recognized method to describe and apply the location of scalp electrodes in the context of an EEG exam. It shows the differences obtained between the tests generated and the anomalies of the test data based on training data. Finally, the results are interpreted and the efficacy of the procedure is discussed.

Translated title of the contributionUnsupervised learning: application to epilepsy
Original languageEnglish
Pages (from-to)20-27
Number of pages8
JournalRevista Colombiana de Computación
Issue number2
StatePublished - Jul 2019


  • Auto-encoding
  • Automatic learning
  • Deep learning
  • Epilepsy


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