Predicción de crisis epilépticas a partir de tipificación de espigas epilépticas y datos del encefalograma

Epilepsy is a disorder of the central nervous system which is characterized by abnormalities in activity brain power, which manifest as seizures, periods of abnormal behavior, or loss of consciousness. Epilepsy is one of the most common diseases in patients of all ages. ages around the world and yet there is no clear idea of ??the factors that trigger their effects. For this reason, this project addresses two major challenges: Typification of epileptic spikes and prediction of epileptic seizures from encephalogram data. With this in mind, for the first Part of the purpose is to identify characteristics in the epileptic spikes, contained in the data of the encephalogram, so that it can be done using the K-means algorithms and AglomerativeClustering. While for the second part predictive models of high interpretability such as Decision Trees and Random Forest. These prediction models are trained with data from encephalograms enriched from data obtained from the models grouping

• Autores: Lobatón Galindo, Juan Guillermo
• Tipo de recurso: Trabajo de grado de pregrado
• Fecha de publicación: 2020
• Institución: Universidad de los Andes
• Repositorio: Séneca: repositorio Uniandes
• Idioma: spa
• OAI Identifier: oai:repositorio.uniandes.edu.co:1992/51472
• Acceso en línea: http://hdl.handle.net/1992/51472
• Palabra clave: Epilepsia; Electroencefalografía; Aprendizaje automático (Inteligencia artificial); Ingeniería
• Rights: openAccess
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/