Unsupervised learning: application to epilepsy
| Autor: | Dewar Rico-Bautista, Paola Andrea Romero-Riaño, Gabriel Mauricio Martinez-Toro, Efrén Romero-Riaño |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
medicine.medical_specialty
lcsh:Computer engineering. Computer hardware General Computer Science education lcsh:TK7885-7895 Context (language use) 02 engineering and technology Neurological disorder Audiology Electroencephalography lcsh:QA75.5-76.95 03 medical and health sciences Epilepsy 0302 clinical medicine 0202 electrical engineering electronic engineering information engineering medicine auto-encoding Training set medicine.diagnostic_test business.industry deep learning medicine.disease medicine.anatomical_structure automatic learning Scalp Recurrent seizures epilepsy 020201 artificial intelligence & image processing lcsh:Electronic computers. Computer science business 030217 neurology & neurosurgery Test data |
| Zdroj: | Revista Colombiana de Computación, Vol 20, Iss 2, Pp 20-27 (2019) |
| ISSN: | 2539-2115 1657-2831 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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