Unsupervised learning: application to epilepsy

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

doi:10.29375/25392115.3718

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 / Notes › Scientific Article › peer-review

Abstract

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 contribution	Unsupervised learning: application to epilepsy
Original language	English
Pages (from-to)	20-27
Number of pages	8
Journal	Revista Colombiana de Computación
Volume	20
Issue number	2
DOIs	https://doi.org/10.29375/25392115.3718
State	Published - Jul 2019

Keywords

Auto-encoding
Automatic learning
Deep learning
Epilepsy

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10.29375/25392115.3718

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abstract = "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.",

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T2 - application to epilepsy

AU - Martínez-Toro, Gabriel Mauricio

AU - Rico-Bautista, Dewar

AU - Romero-Riaño, Efrén

AU - Romero-Riaño, Paola Andrea

PY - 2019/7

Y1 - 2019/7

N2 - 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.

AB - 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.

KW - Auto-encoding

KW - Automatic learning

KW - Deep learning

KW - Epilepsy

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Unsupervised learning: application to epilepsy

Abstract

Keywords

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