A comparative study of CNN-capsule-net, CNN-transformer encoder, and Traditional machine learning algorithms to classify epileptic seizure

A comparative study of CNN-capsule-net, CNN-transformer encoder, and Traditional machine learning algorithms to classify epileptic seizure

Abstract Introduction Epilepsy is a disease characterized by an excessive discharge in neurons generally provoked without any external stimulus, known as convulsions. About 2 million people are diagnosed each year in the world. This process is carried out by a neurological doctor using an electroenc...

Full description

Bibliographic Details
Main Authors: Sergio Alejandro Holguin-Garcia, Ernesto Guevara-Navarro, Alvaro Eduardo Daza-Chica, Maria Alejandra Patiño-Claro, Harold Brayan Arteaga-Arteaga, Gonzalo A. Ruz, Reinel Tabares-Soto, Mario Alejandro Bravo-Ortiz
Format: Article
Language:English
Published: BMC 2024-03-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Capsule-Net
Electroencephalograms
Epilepsy
Machine learning
Transformer Encoder
Online Access:https://doi.org/10.1186/s12911-024-02460-z

Internet

https://doi.org/10.1186/s12911-024-02460-z

Similar Items